Advancing Research on Chronic Conditions in Women (2024)

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8 Multiple Chronic Conditions Previous chapters have described the current knowledge and gaps in the understanding of specific chronic conditions in women. The reality is that most of these conditions do not occur in isolation; many women often experience more than one chronic condition at a time. Multiple chronic conditions (MCC) pose a significant challenge for affected women, health care providers, and health care systems due to the complexities involved in managing multiple conditions. MCC also contribute to reduced quality of life. “Multimorbidity” is another term used interchangeably to describe MCC. This chapter highlights the challenges defining and measuring MCC, biological mechanisms underlying MCC, diagnosis and treatment/management in women, and research gaps. DEFINITION OF MULTIPLE CHRONIC CONDITIONS MCC refers to two or more co-occurring chronic physical or mental health conditions (AHRQ, 2023; Fortin et al., 2010; Mercer et al., 2009; Uijen and Van De Lisdonk, 2008); “comorbidity” indicates a health condition or conditions existing in the context of an index disease (Valderas et al., 2009; Yancik et al., 2007). The associated health and social needs of one or more chronic conditions further influences the complexity of an individual’s situation, and such complexity may require a more expansive coordination of care and long-term health services (McGilton et al., 2018). The definition of MCC has no universally accepted standard, causing both heterogeneity and inconsistencies in defining and measuring MCC in the literature (Yancik et al., 2007). The lack of a standardized definition and use of accurate tools for measuring multiple diseases and their associated complex morbidity have led to variability in study design in epidemiological and mechanistic studies, along with challenges in synthesizing the literature across studies and gaps in knowledge. Inherent in any definition or measurement of MCC is the need to identify the conditions and their number (Griffith et al., 2018; Ho et al., 2021). Choosing an instrument requires matching the purpose of measurement to an appropriate approach and tool, which will be dependent on available data sources and should be informed by contextual and other related constructs to enhance the overall measurement (Griffith et al., 2018; Suls et al., 2021). Another PREPUBLICATION COPY: UNCORRECTED PROOFS 

2 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN term in the literature that has no universal definition is “complex morbidity,” which generally refers to the complex effects that living with MCC can have on the health and well-being of individuals (Pati et al., 2023). MEASUREMENT TOOLS The most common quantification methods of MCC include simple numerical counts from a set of possible chronic conditions considered; weighted counts based on a selected outcome such as mortality; or an assessment of a clustering of conditions (Skou et al., 2022). A 2018 National Institutes of Health (NIH) workshop on measuring multimorbidity identified four purposes for it: (1) describing the current health of a population or subpopulation; (2) identifying multimorbidity as a predictor of mortality, hospitalization, cumulative psychosocial burden, physical disability, or health care costs; (3) testing the role of multimorbidity as a possible modifier (or covariate) of another factor’s contribution to a health-related outcome; and (4) treating multimorbidity as an outcome of other factors. The workshop report recommended that the purpose of multimorbidity measurement should guide decisions related to data sources and instruments (Suls et al., 2021). Measuring MCC depends on the data, which can come from self-reports, physicians’ diagnoses of a list of conditions in a survey, chart review validation of self-reported data, diagnostic claims, or electronic health record (EHR)-based measures (Suls et al., 2021). It also depends on what conditions the measurement is assessing. In a systematic review of 566 studies, the number of conditions assessed in multimorbidity measures ranged from 2 to 285 (Skou et al., 2022). Many studies report on the prevalence of two or more as evidence of MCC (Ho et al., 2021; Skou et al., 2022). However, as the brief lists generally exclude the extent of female- specific and gynecologic conditions, the true prevalence of MCC in women is likely underreported (Skou et al., 2022; Temkin et al., 2023; Valderas et al., 2009). Other measures of MCC are based on a predictive index or score anchored to an outcome such as cost, use, mortality, or function; these scores may include markers of severity of illness, functional status, or social determinants of health (SDOH) (Griffith et al., 2018). The degree to which such measurement tools assess sex and gender differences is variable and not widely studied. It is important to understand the nuances of what is being measured in interpreting results of MCC studies. Many studies have measured MCC using the Charlson Comorbidity Index, a commonly used index that predicts excess mortality resulting from chronic conditions, or indexes derived from it (Charlson et al., 1987; NIH, 2023). Researchers have recognized that functional limitations and geriatric syndromes, both clinical conditions in older persons that do not fit neatly into disease categories, add important information to chronic condition measurement (Fried et al., 2001; Koroukian et al., 2015). A population study using data from the Health and Retirement Study (HRS) defined baseline multimorbidity as the following: 1. the occurrence or co-occurrence of at least one of six chronic conditions: high blood pressure, heart disease, stroke, diabetes, lung disease, and non-skin cancers; 2. the occurrence or co-occurrence of functional limitation in at least one of four categories: standard mobility tasks such as the ability to walk two to three blocks, strength tasks such as the ability to lift 10 pounds, activities of daily living, and instrumental activities of daily living and PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 3 3. the occurrence or co-occurrence of geriatric syndromes in at least one of seven conditions: vision impairment, hearing impairment, moderate or severe depressive symptoms, urinary incontinence, low cognitive performance, persistent dizziness or lightheadedness, and severe pain. The investigators summed the binary indicators for each category—1 if the condition was present, 0 if it was not—and created an ordinal measure of multimorbidity (see Table 8-1) (Koroukian et al., 2015). TABLE 8-1 The number of chronic conditions used to measure baseline multimorbidity in a population health study MMO No chronic conditions, functional limitations, or geriatric syndromes MM1 Occurrence but no co-occurrence of chronic conditions, functional limitations, or geriatric syndromes MM2 Co-occurrence of any two of chronic conditions, functional limitations, or geriatric syndromes MM3 Co-occurrence of all three of chronic conditions, functional limitations, and geriatric syndromes SOURCE: Koroukian et al. (2015). PREPUBLICATION COPY: UNCORRECTED PROOFS 

4 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN Another assessment tool is the Comprehensive Geriatric Assessment, which evaluates functional status, comorbidities, cognitive ability, nutritional status, psychological state, and social support and reviews patients’ medications (Extermann and Hurria, 2007) and was developed to detect problems missed by a regular assessment in geriatric and cancer patients. A systematic review of community and population studies focused on multimorbidity identified at least 35 objective measures, with each using different exposure variables to generate a score or index associated with or without outcomes (Stirland et al., 2020). Figure 8-1 provides a flowchart of the recommended indexes organized by components and original outcomes (Stirland et al., 2020), emphasizing the point that measurement should be guided by the purpose of multimorbidity measurement and an understanding of the nuances of the tools. FIGURE 8-1 Flowchart for measuring multimorbidity indexes proposed by Stirland et al. (2019) SOURCE: Stirland (2020). PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 5 PREVALENCE OF MULTIPLE CHRONIC CONDITIONS The number of U.S. adults with MCC is expected to rise, in part as a result of an aging population, with those aged 65 years and older projected to reach approximately 80.8 and 94.7 million—about 25 percent of the population—by 2040 and 2060, respectively (Ansah and Chiu, 2023). Based on the data from the 2018 National Health Interview Survey (NHIS), 51.8 percent of U.S. adults were diagnosed with at least 1 of 10 selected chronic conditions—arthritis, cancer, chronic obstructive pulmonary disease (COPD), coronary heart disease, asthma, diabetes, hepatitis, hypertension, stroke, and kidney failure—and 27.2 percent had two or more (Boersma et al., 2020). One study based on HRS data from 1998 to 2018 found that the prevalence of one chronic condition in women was higher than in men, but men reported a greater prevalence of MCC (Ansah and Chiu, 2023). A limitation of this finding is that HRS data were only collected for the nine chronic conditions listed and did not capture many common ones more relevant to women. Another study found that the prevalence of MCC is higher among women than men: 28.4 versus 25.9 percent (Boersma et al., 2020). It was highest among non-Hispanic White adults (30.6 percent), followed by non-Hispanic Black (27.0), Hispanic (17.7), and non-Hispanic Asian (16.4) adults (Boersma et al., 2020). It was also higher in adults 65 years and older compared to those 34–64 and 18–44 and among adults living in rural (34.8 percent) versus urban (26.1 percent) areas (Boersma et al., 2020). Data that specifically characterize the prevalence of MCC in women by race, ethnicity, and geographic area were not provided. Another study using NHIS data reported evident disparities in race and ethnic groups, where Black individuals aged 30 years and older had a multimorbidity prevalence equivalent to that of Latino/Hispanic and non-Hispanic White individuals who were 35 years and older and Asian individuals who were 40 years and older, leading the investigators to conclude that MCC affects Black individuals at younger ages (Caraballo et al., 2022). Over a 2-decade period, with increasing multimorbidity prevalence for all groups studied, no significant progress was made in eliminating disparities between Black and White individuals (Caraballo et al., 2022). As care access, and therefore receiving a diagnosis and having it recorded in the EHR or appear in claims data, is one of the main disparities affecting racially and ethnically minoritized populations, this is likely to result in underestimating MCC prevalence among these groups. GENDER DIFFERENCES IN MULTIPLE CHRONIC CONDITIONS Overall, the literature suggests that women are more likely to have MCC than men. A systematic review of international studies found that being a woman, older age, and lower socioeconomic status were determinants of greater multimorbidity (Violan et al., 2014). Based on the findings from a national prospective cohort study of Australian women, the odds ratio for multimorbidity in women was approximately twice as high as the odds of developing only one new condition compared to women who did not develop any new condition (Xu et al., 2018). The study also found that approximately 25 percent of women who were initially diagnosed with stroke developed other conditions at a higher percentage than the 9.9 and 11.4 percent of women initially diagnosed with diabetes or with heart disease (Xu et al., 2018), respectively. PREPUBLICATION COPY: UNCORRECTED PROOFS 

6 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN MCC is also more common in women with some specific conditions than in men, suggesting differences in the drivers of MCC. For example, rheumatoid arthritis (RA) and osteoarthritis have differences based on sex, with women more likely to have multimorbidity (Fernandes and Valdes, 2015; Marshall et al., 2019; Stevens et al., 2023). Differences in multimorbidity between women and men were larger in the RA population compared to those without RA, but in both groups, the difference waned as the number of comorbidities increased with increasing age (Stevens et al., 2023). Types of comorbidities differ between women and men with RA aged 18–50 and older than 51 (Stevens et al., 2023). ECONOMIC EFFECT OF MULTIPLE CHRONIC CONDITIONS IN THE UNITED STATES MCC has profound implications in health care costs and resource use. One approach to measuring the costs of MCC is to define an index condition and calculate the excess costs of it when other conditions co-occur (Sambamoorthi et al., 2015). For example, patients with diabetes and depression had 4.5 times higher health care expenditures than patients with diabetes but without depression (Egede et al., 2002). Patients with COPD and gastroesophageal reflux disease (GERD) had 1.5 times greater expenditures compared to those with COPD and without GERD (Ajmera et al., 2014). Moreover, health care spending depended on both the number and cluster of conditions, with inpatient costs accounting for the largest increase based on a cross-sectional analysis of Medicare, Medicaid, and commercial insurance claims (Hajat et al., 2021). The proportion of total health spending on inpatient costs increased with additional conditions: $527 (12 percent) for two conditions, with a total average health expenditure of $4,385, but $11,763 (34.7 percent) for 11 conditions, with a total average health spending of $33,874 (Hajat et al., 2021). In contrast, the proportion of total health care spending on outpatient services decreased with additional conditions: $2,666 (60.8 percent) for two conditions, with a total average health expenditure of $4385, but $16,933 (50 percent) for 11 conditions, with a total average health expense of $33,874 (Hajat et al., 2021). MULTIPLE CHRONIC CONDITIONS ACROSS THE LIFE COURSE Sex and gender differences in lifetime MCC prevalence depend on the populations, subpopulations, and conditions studied. A scoping review of studies focused on children found that 49 out of 65 did not report on sex or gender (Romano et al., 2021). Cohorts are just emerging to rigorously study multimorbidity in children and understand any sex differences (Ferro et al., 2019). Limited literature focuses on young adulthood through older ages with a life course approach (Romano et al., 2021), and few studies have explored the role of pregnancy, with one small study indicating that MCC was more common with a second pregnancy compared to a first (Pati et al., 2022). A study based on medical records from the Rochester Epidemiology Project found that women with comorbid depression and anxiety had accumulated more chronic conditions, including hypertension, elevated circulating lipid levels, coronary artery disease, and stroke, at younger ages when assessed at 20, 30, and 60 years old (Bobo et al., 2022). Not only are these conditions diagnosed at a younger age, but as women tend to survive longer than men, they will also live with multiple long-term conditions as they age. PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 7 From early to late middle age, it is common for women to experience two or more health conditions, including diabetes, heart disease, and stroke and accumulate more conditions over time (see Figure 8-2) (Xu et al., 2018). MCC, such as heart disease, osteoporosis, fractures, stroke, diabetes, dementia, and cancer, increase after menopause, but it is not fully understood if aging alone plays a primary role or if menopause contributes (Jin, 2022). Among older women, MCC depends on the conditions. Falls, urinary incontinence, osteoporosis, and fragility fractures are more common in women (Gale et al., 2016), and although these are not always included in measures of MCC, they may contribute to the significantly higher prevalence in older women compared to men (Chowdhury et al., 2023). The next section discusses MCC clusters in women. FIGURE 8-2 The proportion of multimorbidity and number of chronic conditions increasing by age group. SOURCE: Barnett et al. (2012). PREPUBLICATION COPY: UNCORRECTED PROOFS 

8 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN BIOLOGICAL MECHANISMS OF MULTIPLE CHRONIC CONDITIONS Several considerations suggest that many diseases share common molecular and sex- biasing mechanisms, leading to co-occurrence of diseases affecting women and multiple intersecting effects of one disease on others. For example, many genes affect two or more seemingly unrelated phenotypic traits, influencing diverse molecular networks that participate in causing or responding to disease. Thus, variations in these genes will simultaneously affect multiple diseases. Numerous chronic conditions have an immune, autoimmune, or inflammatory component; disruption in immune function will influence those conditions in tandem. In addition, the factors that cause sex differences and account for the greater incidence and progression of disease in women relative to men include the effects of gonadal hormones acting on many cell types throughout the body and of specific widely expressed sex chromosome genes that affect basic cellular functions (Arnold, 2022). Thus, disruptions of the sex-biasing mechanisms are likely to have simultaneous effects on many disease processes in diverse tissues. The Role of Hormones on Multiple Chronic Conditions Across the Life-Span Ovarian steroid hormones, including estrogen, androgen, and progesterone, have influential effects on the incidence, severity, and clinical presentation of certain chronic conditions that affect women. These effects result from the fluctuations in hormonal levels and the neuroendocrine feedback mechanisms involved in the menstrual cycle, perimenopause, and menopause. Moreover, sex-specific molecular and clinical studies have identified puberty, pregnancy, and menopause as three windows of vulnerability to chronic conditions in women. Compared to men, women have lower concentrations of circulating androgens, including testosterone, produced by the ovaries and adrenal glands. Androgens serve as precursors for estrogen production and synthesis and play a significant biological role in the maturation processes of ovarian follicles (Daniel and Armstrong, 1986; Gervásio et al., 2014). The decline in androgens that occurs in aging has been associated with impaired sexual function; reduced lean body mass, cognitive function, and psychological and emotional health; and increased bone loss and frailty (Bachmann et al., 2002; Cappola et al., 2009; Davis et al., 1995; van der Made et al., 2009; van Geel et al., 2009). Although testosterone is critical in premenopausal and older women, high testosterone and estradiol and low sex-hormone–binding globulin levels are associated with insulin resistance and diabetes, which are characterized by low-grade inflammation (Horstman et al., 2012). Thus, age-related changes characterized by reduction in sex hormones contribute to a proinflammatory state. Hormonal changes and their potential effects on inflammation may affect conditions such as atherosclerosis, cardiovascular disease (CVD), metabolic syndrome, and Type 2 diabetes (Horstman et al., 2012). Estrogen receptors (ERs) are distributed ubiquitously and involved in complex physiologic mechanisms in women (Paterni et al., 2014). They influence many organ systems including the bones, musculoskeletal system, urinary tract, reproductive tract, cardio vasculature, brain, hair, and skin. Estrogens play a key and changing role in women across the life course, from puberty to menopause. For example, women lose on average 80 percent of their estrogens during the first year of menopause when ovarian function declines, and this can lead to an accelerated decline in bone mass, muscle mass, and muscle strength (Horstman et al., 2012). PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 9 Overall, changes in hormone levels contribute to aging because the endocrine system plays a major role in cellular interactions, metabolism, and growth. Aging in women involves a complex multifactorial process that affects physical, psychological, cognitive, behavioral, sexual, and social functions (Horstman et al., 2012). It is associated with the decline in estrogens and androgens, which may lead to muscle loss or sarcopenia, muscle weakness, decreased functional and cognitive performance, and overall decreased life-span (Horstman et al., 2012). Common hormone-dependent chronic conditions in women include menstrual migraines; depression, including premenstrual syndrome and postpartum and perimenopausal depression; osteoporosis; Alzheimer’s disease (AD); and urinary incontinence. Research has shown that fluctuating sex hormones increase susceptibility to depression based on studies involving female- specific brain plasticity and neuronal gene expression (Kundakovic and Rocks, 2022). In general, osteoporosis disproportionally affects women in developed countries, and fracture rates among women are approximately twice as high as in men (Messina et al., 2004). The cause is complex, but hormonal changes after menopause increase the rate of bone resorption, leading to greater risk of osteoporosis (North American Menopause Society, 2002). AD is more prevalent in women and may be related to the decline in estrogen during menopause (Jung et al., 2008). Estrogen has been shown to be neuroprotective against oxidative stress, excitatory neurotoxicity, and ischemia (Alkayed et al., 2000; Goodman et al., 1996; Jung et al., 2008), leading to the consideration of its use as a potential treatment for AD. However, menopausal hormone therapy did not reduce dementia risk in women in some studies (Henderson, 2006; Jung et al., 2008). In addition, several recent large epidemiologic studies have suggested an association of hormone therapy with increased rather than decreased risk of dementia (Løkkegaard et al., 2022; Rocca and Faubion, 2022; Savolainen-Peltonen et al., 2019). Therefore, the association with dementia remains uncertain and more research is needed. Currently, the use of hormone therapy for the prevention of dementia is only recommended for premature or early menopause, and not for menopause within the normal age range (Kaunitz et al., 2021; North American Menopause Society, 2022). Urinary incontinence is more common during and after menopause and in women than men, implying the critical role of estrogen in genitourinary tissues (Jung et al., 2008). This is supported by evidence of ERs in the urethra and bladder. This association implies that reduced estrogen levels are a factor in urinary incontinence; however, the use of hormone therapy for this condition remains contentious (Jung et al., 2008). While many studies have shown reductions in urinary loss, others have demonstrated either an exacerbation of symptoms or no benefit (Jung et al., 2008; Quinn and Domoney, 2009). Different doses and ratios of hormones as well as methods of delivery (oral versus topical versus vaginal) may account for the discrepancies in clinical findings (Quinn and Domoney, 2009). Accelerated Aging, Epigenetic Clocks, and Multimorbidity Work in gerontology has suggested that biological aging is a potentially modifiable driver of late-life functional decline and chronic diseases (Barnes, 2015; Ermogenous et al., 2020; Kennedy et al., 2014; López-Otín et al., 2013; Skou et al., 2022; Wetterling, 2021). However, it is often difficult to measure this complex biological process before it becomes clinically manifest as a single disease, multimorbidity, functional limitation, or frailty. A large body of work over the last decade has focused on developing reliable measures of biological aging, including differentiating between older and younger persons and describing variations in biological aging among persons of the same chronological age. It is important to separate chronological age from PREPUBLICATION COPY: UNCORRECTED PROOFS 

10 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN biological age, represented by changes at the cellular, tissue, organ, or system levels, to classify someone as aging faster (accelerated aging) or slower (decelerated aging) than their peers. Accelerated aging has been associated with multiple adverse health outcomes, including multimorbidity (Fransquet et al., 2019; Jain et al., 2023; Lu et al., 2019, 2022). Researchers have measured biological aging by examining deoxyribonucleic acid (DNA) methylation, telomere length, and blood-derived biomarkers (Belsky et al., 2017; Justice et al., 2018; López-Otín et al., 2013). Additional hallmarks of aging include genomic instability, epigenetic effects, 1 shortening of telomeres, loss of proper homeostasis of protein production and turnover, altered intercellular communication, mitochondrial dysfunction, dysregulated nutrient sensing, cellular senescence, and stem cell exhaustion (López-Otín et al., 2013). These processes may be possible targets for research aimed at preventing or ameliorating multimorbidity (Ermogenous et al., 2020; López- Otín et al., 2013). Epigenetic clocks serve as promising biomarkers of aging (Faul et al., 2023; Horvath and Raj, 2018; Levine, 2020; Oblak et al., 2021). They track age in multiple diverse tissues and cells, are related to other markers of aging, show predictive power for morbidity and mortality, and appear amenable to intervention (Fahy et al., 2019; Faul et al., 2023; Hannum et al., 2013; Horvath and Raj, 2018; Levine, 2020). Epigenetic clocks are based on integrating DNA methylation data assessed at tens to hundreds of locations across the genome (Horvath and Raj, 2018; Jabbari and Bernardi, 2004; Levine, 2020; Oblak et al., 2021). DNA methylation is usually associated with transcriptional repression through its effect on chromatin organization and thought to control several cellular mechanisms, including differentiation, replication, X chromosome inactivation, stress response, and genomic imprinting. DNA methylation sites accumulate in a predictable pattern with aging, and thus it represents an ideal resource for generating molecular age predictors (Levine, 2020). Given that biological aging itself is unobservable, a proxy variable is necessary; first- generation clocks used chronological age. Epigenetic age acceleration, measured by two first- generation clocks, the Horvath and Hannum clocks, was cross-sectionally associated with body mass index and frailty (Ryan et al., 2020). However, the realization that this is an inadequate proxy led to the second-generation clocks, which were trained to predict correlates of aging. The PhenoAge clock (also known as the “Levine clock”) was created in 2018 to predict phenotypic aging (Levine et al., 2018) and was derived from conventional blood chemistry measures such as glucose, albumin, and C-reactive protein levels, that were combined to generate a robust predictor of mortality. The PhenoAge clock is strongly correlated with chronological age but also ensured that differences among persons of the same age were related to future morbidity and mortality risk; it was shown to be a better indicator than first-generation clocks. The GrimAge clock, the most recent second-generation clock, is a composite biomarker including seven DNA methylation estimators of specific plasma proteins and a DNA methylation estimator of smoking in pack-years. It also includes chronologic age and sex (Lu et al., 2019). First- and second-generation clocks only studied individuals of different ages at one point in time, whereas third-generation clocks, such as the Dunedin Pace of Aging Calculated from the Epigenome (DunedinPACE), added a longitudinal component (Belsky et al., 2022). In HRS, PhenoAge, GrimAge, and DunedinPACE were associated with concurrent cognitive dysfunction and functional limitations and chronic conditions measured 2 years after the initial DNA Epigenetic effects result from changes to the structure of DNA rather than changes to the DNA sequence itself. 1 DNA methylation is an example of an epigenetic change. Epigenetic changes can be passed along to future generations. PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 11 methylation measurement. In addition, these clocks predicted 4-year mortality. However, other factors, such as demographics, socioeconomic status, mental health, and health behaviors, remained equal, if not more robust, predictors of late-life outcomes (Faul et al., 2023). Studies have found differences in epigenetic aging among women versus men. A systematic review of epigenetic clocks that included Horvath, Hannum, Levine, and GrimAge found that epigenetic age acceleration occurred in men (Faul et al., 2023; Oblak et al., 2021). These findings are consistent with the male–female health survival paradox: men have a shorter life-span, but women experience greater disability and poor health (Alberts et al., 2014). Men experience a faster pace of aging before age 50, but the pace in women increases after menopause, reducing the difference in epigenetic age in the later decades of life (Li et al., 2020) (Levine et al., 2016; Oblak et al., 2021). Consistent with this theory, evidence shows that menopause leads to increases in epigenetic age (Levine et al., 2016). A 2016 study found that women who had both ovaries removed before spontaneous menopause had higher levels of DNA methylation in blood- and in saliva-derived DNA, whereas women who experienced spontaneous menopause at younger ages had more DNA methylation in blood-derived DNA (Levine et al., 2016). In addition, cheek tissue samples from women who received menopausal hormone therapy had lower DNA methylation (Levine et al., 2016). A 2019 study from China replicated the association between age of menopause and methylation using DNA from subcutaneous adipose tissue (Lu et al., 2019). These data support the idea that menopause and its reduction in estrogen may accelerate the epigenetic aging process in blood and other tissues (Levine et al., 2016). However, the investigators were uncertain about a possible confounding effect for the association with younger age at spontaneous menopause. It cannot be ruled out that some genetic variants could independently cause both accelerated aging and earlier age at menopause, thus creating a spurious association. Nonetheless, several studies support the hypothesis that postmenopausal women experience accelerated aging, which then confers a greater susceptibility to MCC (Jain et al., 2023; Levine et al., 2016; Lu et al., 2019). In addition a recent study suggests that the number of pregnancies in women is causally associated with acceleration of two epigenetic clocks, suggesting that accelerated aging may be detectable at even younger ages (Ryan et al., 2024). Inflammation Considering that inflammation is one of the major mechanistic drivers of a wide range of individual chronic conditions, including CVD, AD, depression, and endometriosis, associations between the inflammatory process and multimorbidity are also evident (Derry et al., 2015; Furman et al., 2019; Harris et al., 2018). The literature indicates that levels of inflammatory proteins correlate positively with the number of chronic conditions and multimorbidity (Friedman and Ryff, 2012). For example, in the Mayo Clinic Study of Aging, individuals in higher multimorbidity profiles had significantly higher levels of proinflammatory cytokines that included interleukin-6 (IL-6) and tumor necrosis factor-alpha, as compared to participants in lower multimorbidity profiles. Sex stratification of the data showed a significant association between multimorbidity and IL-6 levels in women, but not in men (St. Sauver et al., 2022). The InCHIANTI Study also identified IL-6 as elevated in individuals with higher baseline multimorbidity and that IL-6 levels increased steeply in conjunction with steeper increases in the number of chronic conditions (Fabbri et al., 2015). The latter suggests that the rate of increase of IL-6 may predict the rate of increase in multimorbidity in a given period (Fabbri et al., 2015). PREPUBLICATION COPY: UNCORRECTED PROOFS 

12 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN In the Survey of Mid-Life Development in the United States study, inflammatory markers including, IL-6, C-reactive protein, and fibrinogen, were associated with greater limitations in activities of daily living, suggesting that the inflammatory process may somehow mediate the degree of disability experienced by individuals with multimorbidity (Friedman et al., 2015, 2019). Another research team corroborated this finding, showing that elevated levels of IL-6 and C-reactive protein were associated with higher risk for major mobility disability (defined as the inability to walk 0.25 miles or 400 meters) in adults ages 68 years and older (Beavers et al., 2021). Studies have also found that markers of inflammation, such as neutrophil–lymphocyte and lymphocyte–monocyte ratios, are associated with increases in prevalent and incident multimorbidity and worsened multimorbidity (Cheong et al., 2023). Although correlation does not equal causation, several groups have proposed that inflammatory proteins could exacerbate multimorbidity through their adverse effects on skeletal muscle, such as by promoting breakdown of proteins in muscle and impairing regeneration (Botoseneanu et al., 2023; Friedman et al., 2019; Peake et al., 2010). Presumably, this would lead to higher risks for muscle wasting and frailty, two common features of multimorbidity among older adults. Despite little research investigating differences between women and men in the association between levels of inflammatory markers and multimorbidity, an observational longitudinal study stratified data from HRS by sex and identified differences in the association of biomarker types, such as proinflammatory factors, with certain multimorbidity clusters (Botoseneanu et al., 2023).These results indicated that higher levels of proinflammatory C- reactive protein were associated with higher prospective disability in women with multimorbid conditions, including arthritis, hypertension, heart disease, or lung disease. In contrast, the glycemic biomarker hemoglobin A1c was preferentially associated with disability in men with multimorbidity that included arthritis, diabetes, and cognitive impairment. Although this is only one study, the overall findings hint that inflammation may be more likely linked to multimorbidity in women, and that perhaps men and women exhibit tendencies for certain sex- specific multimorbidity patterns. It is thus important to continue stratifying clinical data by sex and gender to uncover mechanistic differences related to multimorbidity. Adverse Events Related to Medication Use The hazards of potentially inappropriate polypharmacy—the simultaneous use of multiple medications—may increase the risk of adverse events in both men and women with MCC (Brattig Correia et al., 2019; Maxwell et al., 2021; Nguyen et al., 2023; NIA, 2021). Prescribing cascades result when an adverse effect of a drug is treated as a new condition, rather than a side effect, and an additional drug is prescribed, with its own risks of unintended consequences (Rochon et al., 2024; Rochon and Gurwitz, 1997, 2017). For example, calcium channel blockers for hypertension can lead to a prescription for a loop diuretic to treat the common side effect of lower extremity edema. In this example, gender differences in the risk of the second drug were not found (Rochon et al., 2024; Savage et al., 2020). Some data suggest that women use specific classes of harmful medications more often than men (Maust et al., 2021; Orlando et al., 2020). The General Accounting Office found in a 2001 report that of 10 drugs withdrawn from the market since 1997, eight came with greater risks to women, because either they were more likely to be prescribed to women or women had greater risks even when prescribed similarly (FDA, 2013; GAO, 2001). For example, women are more likely to receive benzodiazepines, even though overall use has declined in some populations (Agarwal and Landon, 2019; Edinoff et al., 2021; McHugh et al., 2021; Olfson et al., PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 13 2015), and recent studies have shown that this difference persists in some populations (Olfson et al., 2015; Pétein et al., 2021; Sibille et al., 2023). People with additional chronic conditions that further increase risk of harm, such as falls, poor mental health, sleeping disorders and polypharmacy, have increased likelihood of continued use of benzodiazepines (Pétein et al., 2021). Women are more likely than men to be taking multiple drugs with central nervous system effects (Maust et al., 2017). As one group noted, “Polypharmacy is particularly important for older women because women are more at risk for drug-related adverse events due to sex-related and gender-related considerations,” including greater health care use and likelihood of receiving a chronic disease diagnosis (Bartz et al., 2020; Franconi and Campesi, 2014; Gandhi et al., 2004; Khezrian et al., 2020; Rademaker, 2001; Rochon et al., 2021). Adverse Childhood Experiences, Stress, and Allostatic Load Research has found that adverse childhood experiences (ACEs) are associated with MCC and suggests that allostatic load, the cumulative experience of chronic stress and life events, is one potential mechanism for this. Data from the Nord-Trøndelag Health Study revealed that childhood difficulties were more common among women, smokers, individuals with sleep problems, individuals who engaged in less physical activity, and those with lower education levels, with a much higher odds ratio of onset of multimorbidity in those with more childhood stress (Tomasdottir et al., 2015). Data from the Canadian Longitudinal Study of Aging showed that ACEs were related to multimorbidity via social engagement and allostatic load (Atkinson et al., 2023). Women with ACEs are more likely to experience migraines and depression and other mood and anxiety disorders and to develop cancer, diabetes, heart disease, lung disease, stroke, autoimmunity, substance use disorder (SUD), and gynecologic conditions, such as endometriosis and fibroids, others (Boynton-Jarrett et al., 2011; Dong et al., 2004; Harris et al., 2018; Moussaoui et al., 2023; Nelson et al., 2020; Norman et al., 2012; Simon and Admon, 2023; Springer et al., 2007; Vásquez et al., 2019; Zota et al., 2022). The prevalence of reporting two or more somatic conditions and mental health conditions was higher for middle-aged adults with a history of ACEs compared to those without and for non-Hispanic Black adults compared to non- Hispanic White and Hispanic adults; data were not disaggregated by gender (Vásquez et al., 2019). Investigators have observed sex- and gender-specific effects of ACEs in human studies and animal models. Parental deprivation and maltreatment during childhood, modeled in animal experiments via maternal separation and resource scarcity, is associated with a higher likelihood of anxiety and depressive symptoms in females (Altemus et al., 2014; Bath, 2020; Colich et al., 2017; Ellis and Honeycutt, 2021; Westfall and Nemeroff, 2015). Evidence suggests that ACEs have an etiological underpinning for MCC; however, much of this research did not report on gender differences. Two proposed mechanisms underlying this effect involve inflammation and X chromosome genes. Clinical studies have shown that ACEs related to abuse, household dysfunction, parental absence, and poor parent–child relationships are associated with heightened inflammation later in life, with higher levels of C-reactive protein and IL-6 (Baumeister et al., 2016; Iob et al., 2022, 2022; Lacey et al., 2020). Clinical and population-based studies support the idea that ACEs and chronic systemic inflammation are associated with depression in adults (Haapakoski et al., 2015; Iob et al., 2022; Osimo et al., 2020). PREPUBLICATION COPY: UNCORRECTED PROOFS 

14 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN Epigenetic changes from DNA methylation could be another mechanism to explain the enduring effects of early-life stress. One study found an association between lower levels of an X chromosome-linked gene (methyl-CpG binding protein 2 2) with early life stress and anxiety or depression (Cosentino et al., 2022), suggesting that X chromosome genes—in addition to or independent from sex hormone effects—contribute to these sex-specific vulnerabilities. Cellular Senescence: A Contributing Factor and Therapeutic Target in Multiple Chronic Conditions Cellular senescence serves numerous physiological functions, such as wound healing, tissue regeneration, embryonic development, and antitumor response (Childs et al., 2017). It is part of an organism’s arsenal of homeostatic mechanisms that ensure DNA integrity and that mutations from genotoxic stress are not passed down to cellular progeny via cell cycle arrest (Childs et al., 2017). Cellular senescence may arise as a consequence of natural cellular aging but also in response to stresses, such as oncogene expression, oxidative stress, and radiation exposure (Lelarge et al., 2024). Although senescent cells no longer divide, they remain metabolically active, secreting various factors that trigger localized immune responses. These factors attract immune cells that trigger programmed cell death pathways in senescent cells and clearance of cellular debris; this is followed by cell progenitors repopulating and repairing the damaged tissue areas. However, if senescence is prolonged, detrimental effects to the local microenvironment can result, including a chronic inflammatory state at localized sites and tissue dysfunction (Childs et al., 2017; Ng and Hazrati, 2022; Zhang et al., 2023). This prolonged state of senescence and continuous accumulation of senescent cells in animal models is thought to contribute to chronic conditions, the aging process, and reductions in both life-span and healthspan 3 (Baker et al., 2016; Childs et al., 2017; Lelarge et al., 2024). Researchers have proposed several mechanisms to explain how senescent cells accumulate, including an aging- related decline in immune function and telomere shortening. Different approaches to reverse or prevent senescence or remove senescent cells have led to remarkable benefits in animal models of different diseases, including atherosclerosis, osteoarthritis, cataracts, cancer, renal dysfunction, and muscle wasting (Baker et al., 2008, 2011; Childs et al., 2016, 2017; Jeon et al., 2017). Many of these conditions co-occur at later ages, suggesting a potential common and effective therapy for ameliorating MCC. This principle was first demonstrated by findings showing that eliminating senescent cells delayed aging-related deterioration of organs and extended the life-span in normally aging mice (Baker et al., 2016; Baker et al., 2008; Baker et al., 2011). Later studies in a mouse model of atherosclerosis showed that removing senescent cells from atherosclerotic plaques promoted stable plaque formation, characterized by a thick fibrous cap that is less prone to rupture (Childs et al., 2016). Similarly, clearance of senescent cells helped repair damaged cartilage in a mouse model of osteoarthritis (Jeon et al., 2017). Based on these findings, researchers have developed several therapeutic approaches using compounds, known as “senolytics,” over the past decade to remove senescent cells (Childs et al., 2017). Perhaps the most promising is dasatinib plus quercetin (D+Q), as numerous independent researchers have demonstrated improvements in different disease contexts (Kirkland and 2 methyl-CpG binding protein 2, also known as “MECP2,” is a regulator of gene expression in the brain. 3 Healthspan refers to the number of years a person remains healthy and free from disease (Childs et al., 2016). PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 15 Tchkonia, 2017), such as improving cognitive function in a mouse model of AD (Zhang et al., 2019) and decreasing senescence markers and senescence-associated secretory phenotype factors in patients with diabetic kidney disease in an open-label Phase 1 pilot clinical study (Hickson et al., 2019). Studies are assessing D+Q therapy in several ongoing clinical trials to treat chronic kidney disease, AD, osteoporosis, and frailty (Lelarge et al., 2024). Those studying D+Q believe it inhibits cell survival pathways induced in senescent cells (Lelarge et al., 2024). Fisetin, a natural flavonoid polyphenol, is another promising therapeutic that studies have shown can curb senescent cell accumulation in a mouse model of aging (Yousefzadeh et al., 2018). It is being tested as a potential treatment for osteoarthritis and frailty in Phase 1 and 2 clinical trials (Lorenzo et al., 2023). More recently, immunological approaches are being developed to clear senescent cells. They use patient-derived cytotoxic T cells with chimeric antigen receptors, antibody-drug conjugates, or vaccines that would recognize senescence-specific cell surface markers, thereby targeting senescent cells for immune-mediated destruction (Amor et al., 2024; Lelarge et al., 2024). However, the existence of markers unique to senescent cells has yet to be confirmed (Baker et al., 2011; Huang et al., 2022). As more evidence points to cellular senescence playing a causal role in MCC, selectively targeting senescent cells for degradation with a broad spectrum agent may attenuate multiple disease processes at once. However, considering that cellular senescence is an evolutionarily conserved mechanism with numerous beneficial functions, this should be approached with caution, as interference with normal homeostatic mechanisms could lead to off-target adverse effects (Childs et al., 2017; Huang et al., 2022). Results in mouse models show no detrimental effects of repeatedly removing senescent cells (Baker et al., 2016; Baker et al., 2011; Childs et al., 2016; van Deursen, 2014), indicating that this approach still holds much promise as an effective treatment for people with MCC. It is still premature to unequivocally make any determinations about sex differences in efficacy or benefit–risk ratios for these agents. However, as studies have found sex differences in the response to some of the inducers of senescence, such as DNA damage (Ng and Hazrati, 2022) and considering the precedents for sex-specific differences in drug responses (Bale, 2019; Whitley and Lindsey, 2009), it is likely that biological sex will influence treatment effectiveness of these promising therapies. Furthermore, as with other drugs, the mode of action of a particular agent may target biochemical pathways distinct to one sex, thus rendering it ineffective in the other sex. Future experiments will need to address whether agents that clear senescent cells can improve MCC and to determine which treatments would be most effective in women. EXAMPLES OF MULTIPLE CHRONIC CONDITIONS CLUSTERS “…there are a lot of different comorbidities that people do not understand or know that are related to their disease. A big one is heart disease…because of inflammation. I think that the health care system could prioritize…understanding how one might be related to another because it might be overlooked.” –Presenter at Committee Open Session Several clusters of conditions are described next that illustrate many of the concepts, the challenges that result from MCC for women, and research gaps. Common combinations of conditions in women likely exist that have yet to be studied robustly enough, so absence of PREPUBLICATION COPY: UNCORRECTED PROOFS 

16 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN conditions from this section does not signify unimportance and instead may indicate a need for more research. In general, the number of chronic conditions increases as men and women get older, with data suggesting sharper increases over time in women (Barnett et al., 2012; Rocca et al., 2014). Research has shown that certain dyads or triads (combinations of two or three chronic conditions, respectively) from a list of 20 chronic conditions deemed as public health priorities in 2010 by the Department of Health and Human Services (Goodman et al., 2013) may occur more frequently in women (Bobo et al., 2016; Rocca et al., 2014). For example, a study evaluating multimorbidity prevalence in Olmsted County, MN, using data from an established records-linkage system, suggested that women experienced more dyad and triad combinations that included arthritis, asthma, dementia, depression, and osteoporosis compared to men, whereas men tended to experience clusters that included cancer, coronary artery disease, and SUD (Rocca et al., 2014). Older adults often had dyads or triads of cardiometabolic conditions, which to a certain extent is expected, considering the shared aspects of this disease grouping (Rocca et al., 2014). However, less common, unrelated combinations were also observed, suggesting that certain mechanisms could underlie the development of each. One idea is that treating one condition could lead to developing or exacerbating of other chronic conditions (Rocca et al., 2014; Uhlig et al., 2014). SUD, Mental Health Conditions, and Human Immunodeficiency Virus (HIV) Mental health and HIV have a bidirectional relationship: SUD involving intravenous drug use is a risk factor for HIV, and individuals living with HIV may develop co-occurring SUD and mental health conditions such as depression (Alpren et al., 2020; Campbell et al., 2017; Chander et al., 2006; Schwetz et al., 2019; Vagenas et al., 2015). In a multisite cohort of 1,027 U.S. women living with HIV, 82.6 percent had one or more lifetime psychiatric diagnosis and SUD, with mood disorders, anxiety disorders, and SUD being most common (Cook et al., 2018). The challenges that women with SUD and mental health conditions face are complex, multifactorial, and different across the life span, creating challenges for treating and caring for them (Springer et al., 2020a). Studies have found that diagnosing and treating concurrent SUDs and mental health conditions are important factors for improving HIV care and prevention (NASEM, 2018, 2020; Springer et al., 2012a; Springer et al., 2020b; Strathdee et al., 2020). Achieving viral suppression, the goal of anti-retroviral therapy (ART), can be delayed or difficult in persons with comorbid SUD and mental health conditions as a result of lower retention and adherence to pre-exposure prophylaxis and ART (Pence et al., 2007). Studies have shown that medication and behavioral treatment for opiate use disorder and stimulant use disorders are effective in reducing HIV risk, transmission, and acquisition, and promoting viral suppression; improved efforts are needed to translate these treatments for women in clinical HIV care settings (Altice et al., 2011; Gowing et al., 2011; McNamara et al., 2021; Nance et al., 2020; Pollock et al., 2020; Silverman et al., 2019; Springer et al., 2012b, 2018; Taweh et al., 2021; Wagman et al., 2020). Evidence-based HIV and drug treatment services tailored to meet women’s needs are limited in the United States (Greenfield et al., 2007). Systemic, structural, social, and cultural barriers limit access to HIV, SUD, and mental health treatment and have compounding effects on the difficulty of accessing care for these MCC in women (Greenfield et al., 2007). Integrated models of care and services are an evidence-based strategy important for improving mental health conditions and HIV outcomes (Hill et al., 2023). These strategies include using telehealth (see Chapter 9) and mobile health services to improve access to PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 17 prevention and treatment services for SUD, HIV, and mental health conditions, along with more low-barrier services and women-specific programs at brick-and-mortar clinics via extended hours, transportation access, and attention to child care needs, and understanding and addressing the power imbalance women face with male partners (Greenfield et al., 2007; Hill et al., 2023; Springer, 2023; Strathdee et al., 2020). In addition, improved services to address trauma; increased access to medication and behavioral health treatments; HIV testing; harm reduction services, such as syringe services programs, naloxone spray, and drug testing for fentanyl and xylazine; reduced barriers and stigma that impede access to and retention on treatment for SUD and HIV prevention and treatment; and improved structural and policy barriers that further impede access to services are all needed to better care for women with SUD, HIV, and mental health conditions (Greenfield et al., 2007; Hill et al., 2023). It is critical to understand, acknowledge, and address their specific needs. Systemic Lupus Erythematosus (SLE) and CVD Patients with SLE have a more than threefold increased risk of a CVD-associated event and increased mortality from hypertension, vascular dysfunction, and myocardial infarction (Ajeganova et al., 2021; Wilhelm and Major, 2012; Zeller and Appenzeller, 2008). The risk of SLE is nine times higher for women (Corker et al., 2023), although both sexes have increased risk for CVD-related mortality (Bartels et al., 2014). SLE severity is linked to a higher risk of negative CVD outcomes in both sexes, with chronic inflammation being a potential mechanism (Corker et al., 2023). Data suggest that men with SLE have a greater predisposition to and more severe disease presentation of CVD compared to women with SLE, although the sex-dependent mechanisms behind this remain unclear (Corker et al., 2023; Crosslin and Wiginton, 2011; Ramírez Sepúlveda et al., 2019). Studies in individuals who do not have SLE have indicated that despite similarities in the pathological end point, the pathway and signaling mechanisms for cardiac complications that stimulate disease progression differ between the sexes (Deleon-Pennell et al., 2018). Whether this is true in SLE patients is not known, but because of sex differences in SLE pathology, the pathway to CVD progression likely differs. Interrogating signaling mechanisms that may differ in men and women with SLE could provide invaluable information to guide developing patient- specific therapeutics. Polycystic Ovary Syndrome, Obesity, and Metabolic Syndrome in Perimenopause As mentioned in previous chapters, the reproductive window is a risk factor for chronic conditions. Polycystic Ovary Syndrome (PCOS) is a hormone-related condition that affects reproductive-aged women and its cardiometabolic comorbidities increase CVD risk in later life (Guan et al., 2022; Sharma and Mahajan, 2021). This is explained by the metabolic disturbances and changes in hormonal profile commonly seen in women with PCOS. For example, the excess production of androgens in addition to normal ovarian production persists even after perimenopause (Guan et al., 2022; Sharma and Mahajan, 2021). Levels of androgens also remain high up to menopause (Sharma and Mahajan, 2021). As women become more androgenic, insulin resistance, chronic inflammation, abdominal adiposity, and elevated blood lipid levels tend to worsen (Sharma and Mahajan, 2021). It seems likely that metabolic disorders, enhanced ovarian androgen secretion, and chronic inflammation in premenopausal women with PCOS persist after menopause, emphasizing lifelong health risks related to this syndrome. It is PREPUBLICATION COPY: UNCORRECTED PROOFS 

18 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN unknown whether PCOS itself or associated comorbidities mediate the increased risk of outcomes associated with CVD (Guan et al., 2022). “Perimenopause,” refers to the natural transitional period to menopause, which marks the end of the reproductive years. It is a critical time for women, not only because they experience bothersome vasomotor symptoms that affect their quality of life, but also because the risk accelerates for cardiometabolic diseases, such as obesity, Type 2 diabetes, CVD, nonalcoholic liver disease/metabolic-associated fatty liver disease, and metabolic syndrome (Jeong and Park, 2022). Cardiometabolic changes, including body fat deposition, that contribute to increased central fat stores and increased metabolic syndrome risk have also been attributed to this transition independently of aging (El Khoudary et al., 2020; Jeong and Park, 2022). In addition, the Study of Women’s Health Across the Nation demonstrated that lipoprotein levels increase dramatically from the year before to the years after the final menstrual period. The transition could trigger an inflammatory response that may modify high-density lipoproteins and contribute to a woman’s atherosclerotic risk at midlife (El Khoudary et al., 2022). Post-Traumatic Stress Disorder (PTSD), Hypertension, Heart Attack, and Stroke Multiple retrospective studies have demonstrated a link between PTSD and a 30–45 percent increase in CVD events or cardiac-specific mortality after adjusting for depression, and demographic, clinical, and psychosocial factors (Akosile et al., 2018; Edmondson et al., 2013; Roy et al., 2015). The causal mechanisms driving this association are unknown, leaving patients vulnerable to CVD. To determine potential differences in women and men, one group evaluated emergency department patients following trauma exposure and noted significant differences in autonomic functioning. Whereas men demonstrated an elevated blood pressure response, women showed an elevation in heart rate 2 weeks post-trauma (Seligowski et al., 2021). An 8-week follow-up demonstrated that women diagnosed with PTSD had lower heart rate variability—a sign of current or future health problems—than men and non-PTSD-afflicted women (Seligowski et al., 2021). Similarly, in a study that evaluated muscle sympathetic nerve activity and multiunit action potentials during a cold pressure test, women with PTSD exhibited a greater pressor response and an exaggerated sympathetic neural recruitment pattern during stimulation of sympathetic nerve activity (Yoo et al., 2020). Rodent models of single severe stress and chronic stress exposure suggest that PTSD dysregulation induces long-term alterations in heart rate variability (Finnell et al., 2018; Koresh et al., 2016) and muscle cell function (Heinrichs, 2014), although measures beyond basic cardiovascular parameters are needed to examine the effects on cardiac structure and remodeling. Clinical and animal studies have demonstrated that chronic stress reprograms immune cells toward a hyperinflammatory phenotype (Barrett et al., 2021). One mechanism by which PTSD may increase CVD risk is epigenetic regulation of immune cell populations (Barrett et al., 2021). Epigenetic studies have demonstrated that PTSD etiology has downstream functional effects on the immune system by reducing methylation levels of immune-related genes (Smith et al., 2011; Uddin et al., 2010). A systematic review that evaluated the temporal relationship between PTSD and CVD demonstrated that 38.6 percent of the studies focused predominantly on men while 17.6 percent focused predominantly on women (Hunter et al., 2023). Around 41 percent of the studies reported on both sexes, although most did not identify gender differences in the link between PTSD and CVD or failed to report race and ethnicity. Investigating the role of sex, gender, race, PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 19 and ethnicity on the temporal relationship between PTSD and CVD are promising avenues for future research. No studies included transgender participants. Osteoporosis, Falls, Sarcopenia, and Frailty The intersection between falls and osteoporosis provides an important cluster of conditions that commonly occur together with significant impact in women. Consistent evidence shows that although both men and women can experience osteoporosis, falls, sarcopenia, and frailty, the prevalence and impact are greater for women (Greco et al., 2019; Park and Ko, 2021). These conditions often occur in combination and yet are not included in many MCC indexes. Frailty is most often considered to be distinct from specific diseases, and therefore distinct from MCC, although it can and does co-occur with chronic conditions (Fried et al., 2004). The differences in frailty between men and women are complex (Park and Ko, 2021). Community- dwelling women aged 65 years and older have a higher prevalence and greater experience of frailty compared to men of the same age (Gordon et al., 2017; Park and Ko, 2021) Among 3,079 community-dwelling older adults from the 2007–2010 National Health and Nutrition Examination Survey, frailty was more prevalent in women, at 8.8 percent versus 5.4 percent in men (Zhang et al., 2018). Differences in prefrail older adults by sex has been identified in a meta-analysis of 240 studies from 62 countries, regardless of the frailty measure used (O’Caoimh et al., 2021; Park and Ko, 2021). The Hertfordshire Cohort of Aging is an example of a study that has documented the co- occurrence of osteoporosis and sarcopenia with frailty, with increased odds in people with either and both osteoporosis and sarcopenia (Laskou et al., 2022). The English Longitudinal Study of Aging found gender differences in the incidence of falls and variability in the risk factors, many of which are MCC. Although severe pain and diagnosis of at least one chronic condition were independently associated with falls in both men and women, women experienced a greater odds of incontinence and frailty (Gale et al., 2016). Falls in combination with osteoporosis increase vulnerability to injury, and falls and resultant injuries are a major risk factor for functional decline and mortality, with mean overall 1-year mortality after hip fracture of 22 percent and a range from 2.4–34.8 percent. (Downey et al., 2019; Okike et al., 2017). The co-existence of this combination of conditions points to the need for interventions to improve frailty, bone health, and sarcopenia and reduce falls and fear of falling. The role for preventive programs across the life-span, particularly in the postmenopausal period, also merits further research and focus to identify effective strategies to improve outcomes in older women. Visual Impairment, Falls, and Aging Visual impairment, defined by a decline in visual acuity, has adverse effects on quality of life as individuals age and contributes to increased morbidity in the later stages of life (Swenor et al., 2020). Its causes range from uncorrected refractive error to progression of diseases such as cataract, glaucoma, diabetic retinopathy, and age-related macular degeneration (GBD 2019 Blindness and Vision Impairment Collaborators, 2021; NASEM, 2016). Some of these conditions may be corrected with surgery or managed with medicine. However, conditions such as glaucoma and macular degeneration may lead to permanent loss of vision if diagnosed late or the disease process is treatment resistant (GBD 2019 Blindness and Vision Impairment Collaborators, 2021). As these conditions are age related, women are particularly at risk given PREPUBLICATION COPY: UNCORRECTED PROOFS 

20 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN their longer life expectancy compared to men (GBD 2019 Blindness and Vision Impairment Collaborators, 2021; USA Facts, 2023). Uncorrected refractive error, cataracts, and macular degeneration are associated with visual impairment (Congdon et al., 2004; GBD 2019 Blindness and Vision Impairment Collaborators, 2021; Klein et al., 2003; Vitale et al., 2006). It is estimated that uncorrected refractive error represents 83.3 percent of visual impairment, and cataracts account for 50 percent of correctable eye conditions (Congdon et al., 2004; Vitale et al., 2006). Macular degeneration, a leading cause of blindness globally, negatively affects reading, mobility, and emotional scores. It is also important to recognize the link between glaucoma and gender differences. The Rotterdam Eye Study in the Netherlands found a higher risk of open-angle glaucoma in women who had their ovaries surgically removed before age 45 compared to women in older age groups (Higginbotham, 2004; Hulsman, 2001). Studies are needed to further uncover ways that hormonal changes may result in physiological changes in the eye (Higginbotham, 2004). These changes can also modify the patient-centered outcomes expected following a procedure. Research has linked visual impairment to frailty and cognitive decline (Klein et al., 2003). In a cohort study of older women enrolled in the Women’s Health Initiative observational study, visual impairment was associated with a two- to fivefold increase in AD and dementia (Tran et al., 2020). When visual impairment is augmented by two or more chronic conditions, it has an enhanced negative effect on quality of life. In a study using NHIS data from 2002 to 2014, individuals with MCC, including hypertension, heart disease, pulmonary disease, and diabetes had greater odds of visual impairment and likelihood of emergency department visits and hospitalizations compared to healthy individuals (Zheng et al., 2020). This study controlled for gender in its analysis (Zheng et al., 2020). A National Academies consensus study, Making Eye Health a Population Health Imperative (NASEM, 2016) emphasized the multiplier effect of visual impairment when added to chronic conditions. In a study of individuals aged 65 and older, the difficulty of performing both physical and social tasks increased for individuals with visual impairment along with another disease. For example, when individuals reported severe depression, they were 19.5 and 23.9 times more likely to experience difficulty with physical tasks and socializing, respectively, when they had visual impairment (Crews et al., 2006; NASEM, 2016). Visual impairment has been associated with more cognitive decline, and targeting these conditions together shows promise for improving outcomes for older women (Nagarajan et al., 2022; Whitson et al., 2013). The impact of visual impairment on the risk of falls among older adults is of great concern. In one study conducted in India on individuals over 60 (two-thirds of participants were women), those with visual impairment had a 1.47 greater odds of falls compared to those without (Marmamula et al., 2020). Uncorrected refractive error was the most common cause of visual impairment. The prevalence of falls was highest among those individuals with impaired vision or blindness (Marmamula et al., 2020). The fear of falling, exacerbated by visual impairment, is associated with risk of frailty and can further isolate individuals and hinder their ability to perform basic daily functions (de Souza et al., 2022). Underlying contributors to visual impairment risk are multifactorial and have been overlooked because of unintentional lack of awareness. One group developed a framework that considers both personal and environmental factors for assessing the effect of visual impairment on older adults (Swenor et al., 2020). Personal factors, such as socioeconomic status, may exacerbate some of the contributors to visual impairment. Environmental factors, such as the PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 21 physical environment at home and in the neighborhood, are also important. These contribute to health outcomes, representing changes in health status, such as mobility or ability to live independently. The recognition of visual impairment as a critical contributor to the health outcomes of women as they navigate the life course presents opportunities for innovative approaches to identify strategies to prevent further decline at the most vulnerable stage of life. Given the adverse amplification of the intersection of visual impairment and chronic conditions and the longer life expectancy of women in general, additional research on their life course is needed. BIOMARKERS FOR MULTIPLE CHRONIC CONDITIONS Metabolomics has been used to identify biomarkers and their association with different multimorbidity patterns. In the Seniors-ENRICA-2 cohort in Spain, researchers analyzed biological samples from over 700 older adults using high-throughput proton nuclear magnetic resonance metabolomics. Biomarkers groups were identified with exploratory factor analysis, and multimorbidity was classified into three types: cardiometabolic, neuropsychiatric, and musculoskeletal. Different metabolomic biomarkers are associated with different multimorbidity patterns, so developing a complete picture of the molecular mechanisms of multimorbidity will require multiple biomarker measurements (Vázquez-Fernández et al., 2024). Another study used baseline untargeted plasma metabolomics profiling covering more than 1,000 metabolites as a comprehensive readout of human physiology. The investigators used the profiles to characterize pathways associated with and across 27 incident noncommunicable diseases (NCDs) assessed with EHR hospitalization data and cancer registry data from over 11,000 participants. They found 420 metabolites shared between at least two NCDs, representing 65.5 percent of all 640 significant metabolite–disease associations. The results showed that liver and kidney function, lipid and glucose metabolism, low-grade inflammation, surrogates of gut microbial diversity and specific health-related behaviors are antecedents of common NCD multimorbidity that have potential for early intervention and prevention (Pietzner et al., 2021). Researchers have also used U.K. Biobank data to show that multimorbidity was more common in metabolically favorable subgroups despite lower disease impact overall, with a higher relative risk of MCC in the absence of obvious metabolic dysfunction (Mulugeta et al., 2022). Overall, the findings of a preprint scoping review (Spencer et al., 2020) were that higher quality and more longitudinal research is needed, with most studies from European or North American populations. This review did note that obesity was associated with increased multimorbidity. Other results were more varied, reflecting the diverse range of biomarkers investigated and lack of a standard multimorbidity definition. Researchers have conducted limited research on biomarkers for predicting multimorbidity (Spencer et al., 2020). DISPARITIES AND STRUCTURAL/SOCIAL CONTEXTS Lifestyle Behaviors Factors such as chronic stress, poor sleep, physical inactivity, and smoking are behavioral and contextual lifestyle factors related to multimorbidity, and the inability to effectively improve them furthers disparities. Other studies have shown that multiple lifestyle factors together PREPUBLICATION COPY: UNCORRECTED PROOFS 

22 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN increase the incidence of multimorbidity (Fortin et al., 2014; Freisling et al., 2020; Sakakibara et al., 2019; Wikström et al., 2015; Zhou et al., 2023). Women who were physically inactive, smokers, or diagnosed with other medical conditions had higher odds of diabetes, heart disease, and stroke multimorbidity over the next 3 years than women who were not (Xu et al., 2018). The best methods for improving physical inactivity, smoking cessation and intervening on stress management and sleep hygiene merit study for improving quality of life and clinical outcomes for people with multimorbidity and eliminating disparities (Niebuur et al., 2023). Structural Factors As mentioned in previous chapters, individuals who experience discrimination due to multiple intersectional parts of their identities, such as gender, race, ethnicity, sexuality, age, geography, and socioeconomic status, have the greatest degree of disparities in health care access, quality, and outcomes (Pérez-Stable and Webb Hooper, 2023; WHO, 2008). Women with MCC need to seek care more often than women without it, and thus multimorbidity currently increases the risk of disparities in care (Bartz et al., 2020; Hossain et al., 2021). Women more often experience nonfinancial barriers to treatment, such as caregiving and transportation (KFF, 2015). Disparities for transgender and gender-diverse individuals, due to biases and discriminatory experiences, such as the use of the wrong pronouns, may lead to avoiding needed care. Incorporating gender diversity in research, education, and clinical practice to adequately care for sexual and gender identity groups is needed (Ard and Keuroghlian, 2018; Bartz et al., 2020; Krieger, 2003; Rich-Edwards et al., 2018). Neighborhood Environment, Income, Education Consistent evidence shows that socioeconomic deprivation, measured at the individual and neighborhood levels, is associated with higher risk, prevalence, and earlier onset of multimorbidity (Barnett et al., 2012; Pathirana and Jackson, 2018; Takahashi et al., 2016; Violan et al., 2014). Studies have shown that neighborhood deprivation is linked to a higher odds of multimorbidity (Chamberlain et al., 2020; Ingram et al., 2020). One group found that individuals in Scotland with the greatest level of deprivation based on socioeconomic status experienced multimorbidity 10 years earlier than less-deprived people (Barnett et al., 2012). A study using the Area Deprivation Index, a composite measure of neighborhood socioeconomic disadvantage, showed that higher scores were associated with an increased odds of multimorbidity among U.S. adults (Chamberlain et al., 2020). Compared to individuals with the lowest scores, those in the highest category had a 1.5-fold higher odds of multimorbidity and a 1.67-fold higher odds of severe multimorbidity (five or more chronic conditions) (Chamberlain et al., 2020). Those in the most deprived areas had the highest prevalence or incidence of multimorbidity (Ingram et al., 2020). Associations between deprivation and multimorbidity differed by age and multimorbidity type (Ingram et al., 2020). The neighborhood environment has also been linked to engaging in lifestyle behaviors that may benefit or harm health. In the Canadian Community Health Survey study, lower neighborhood walkability measures by the lowest quintile were related to a greater risk of multimorbidity (Moin et al., 2021). At the individual level, a systematic review and meta-analysis of 10 studies found that lower educational attainment was associated with 1.64-fold higher odds of multimorbidity, but this analysis had substantial heterogeneity (Pathirana and Jackson, 2018). A review of over 40 PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 23 studies from North America, Europe, and Australasia found the odds of multimorbidity were up to 4.4 times higher for participants with the lowest income compared with the highest income, and people living in the most deprived areas had the highest odds (Ingram et al., 2020). Although robust evidence of the role of neighborhood and socioeconomic status on the development of MCC was presented, this synthesis of studies did not examine differences by gender in the individual studies, suggesting an area for further research. TREATMENT AND MANAGEMENT OF MULTIPLE CHRONIC CONDITIONS Women living with MCC are at increased risk of death, poorer quality of life, and functional decline and have higher rates of adverse effects of treatments or interventions compared to women without MCC (Davis et al., 2017; Ellingrud et al., 2024; Newman et al., 2020; Temkin et al., 2023). Much of clinical medicine is based on a single disease-approach, with most practice guidelines focused on single conditions, and with limited attention to the experience of MCC (Boyd et al., 2005; Boyd and Kent, 2014; Uhlig et al., 2014). Living with MCC is associated with complex and multiple treatment regimens, which has implications for adherence, prioritization of care plans, and risk of adverse events (Sheehan et al., 2019; Skou et al., 2022; Wolff and Boyd, 2015). Despite increasing consensus that a person- and family- centered approach is best for people living with MCC, as noted in guideline and consensus statements, the best approaches to decision making and clinical management of older adults with MCC remain unclear (Skou et al., 2022). In addition, women, compared to men, have demonstrated a greater propensity for health care seeking, which could enable earlier detection of some conditions (Glynn et al., 2011). Well-designed care for people living with MCC is a challenge for both men and women (Skou et al., 2022). Given evidence to suggest that women are more likely to experience MCC across the life course and may have different combinations of conditions contributing to it, much remains to be learned on how to improve care for them (Carcel et al., 2024). As women experience unique risk factors associated with certain life course stages that confer susceptibility to chronic conditions, timely strategies that focus on risk factor management may prevent or delay MCC (Carcel et al., 2024). As noted earlier in this chapter, research has shown that the arrhythmia and osteoporosis dyad occurred at a fivefold higher rate in women compared to men, with the authors postulating that arrhythmia may be an unintended consequence of bisphosphonate use for osteoporosis (Rocca et al., 2014; Sharma et al., 2014). Recognizing uncommon and unrelated combinations of chronic conditions in women and understanding their associations could thus help guide treatment approaches for MCC and determine the type of care. Understanding which chronic conditions in women are concordant (discordant) and share (do not share) care goals should therefore be prioritized (Magnan et al., 2015; Ricci-Cabello et al., 2021) As women with chronic conditions have complex care needs, it is important for health care systems to adapt to these challenges and address MCC in a coordinated and holistic manner (Temkin et al., 2023; van der Aa et al., 2017). Further research is needed, as many studies have used a list of conditions that may not be tailored for women or include conditions that are specific to women, more common in women, or differentially impact women. Implementing integrated models of care for women with MCC is challenged by the fragmentation of the U.S. health care system, the underreimbursement of cognitive specialties that work to address MCC, and differences in communication and biases as women seek medical PREPUBLICATION COPY: UNCORRECTED PROOFS 

24 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN care. Differences in fragmentation by gender is relatively understudied (Cabana and Jee, 2004; Hussey et al., 2014; Kern et al., 2017, 2018, 2019, 2021; Liu et al., 2010; Nyweide et al., 2013; O’Malley and Reschovsky, 2011; Prior et al., 2023; RWJF, 2010; Romano et al., 2015; Saultz, 2005; Temkin et al., 2023). Care fragmentation is associated with lower rates of recommended care and greater drug–drug interactions, radiology tests, procedures, emergency department visits, and hospitalizations. Cognitive specialties that typically care for the complexity of MCC have lower earning potential than other specialties (Goodson et al., 2019; Kayser, 2023). Bidirectional communication-related behaviors and attitudes toward the gender of both the patient and the provider can affect care. The patient agenda that is elicited, content of conversation, style of communication, content of dialogue, length of visit, nonverbal communication, incorporation of visit companions and power dynamics are influenced by the genders of both patient and physician (Sandhu et al., 2009; Wolff and Roter, 2011). Female patient–doctor dyads may provide more patient-centered care (Sandhu et al., 2009). These factors contribute to disparities in care. RESEARCH GAPS Definition of Multiple Chronic Conditions Challenges in measuring multimorbidity have created gaps in research that have made it difficult to assess patient-oriented outcomes from clinical and population studies including poor understanding of a particular disease, limited or misdirected treatment development, and limited or ineffective treatment options. Moreover, challenges in translational research to inform implementation are also evident as a result of the lack of computational models of complex morbidity into health systems without considering biological and social context, such as age, sex, gender and factors related to SDOH. Limited Animal Models of Multimorbidity There are insufficient animal models for multimorbidity. For example, despite many different animal models of SLE, few replicate the diverse pathological response found in SLE patients, such as that not all SLE mouse models show the same cardiovascular pathology. All research using these models must be tailored to the specific SLE question, but that can be limiting as not all SLE patients have the same outcomes. Population Health Research A common theme of this chapter is that understanding multimorbidity in women depends on which conditions are studied and which are left out, how they are measured, and in what populations they are examined across the life-span. How these measures are used in other types of research, including basic biology, preclinical research involving biomarkers, and clinical studies, has further implications for what is known and unknown. It is important to study the full range of female-specific and gynecologic and conditions that predominantly impact or affect women differently in population research to understand the impact of disease and impacts on quality of life and function. Knowledge about the true prevalence of MCC is necessary to appropriately guide inclusion across life-span initiatives that aim to enroll a representative population of women in PREPUBLICATION COPY: UNCORRECTED PROOFS 

MULTIPLE CHRONIC CONDITIONS 25 clinical trials of pharmacological, surgical, procedural, and health system interventions. Also needed are analytic plans that allow for understanding gender differences in etiology, progression, or treatment. People with MCC are not enrolled in representative numbers in clinical trials, creating a very large evidence gap for guiding the care of this increasing population. Exclusion of Individuals with Multiple Chronic Conditions from Research Studies As the number of individuals with MCC increases, high-quality studies such as randomized controlled trials (RCTs) are of utmost importance. It is evident in the literature that clinical research excludes participants with comorbidities. The discouraging results of a systematic review limited to high-impact journals indicated that up to 81 percent of RCTs reviewed excluded participants with MCC and only 2 percent explicitly included them (Stoll et al., 2019; Van Spall et al., 2007; Yancik et al., 2007). A study examining clinical trials found that the majority of patients with the relevant condition would have been excluded. A quarter of the trials studied excluded over 90 percent of patients living with a condition, more than 50 percent excluded at least three-quarters, and most trials excluded at least half (He et al., 2020). The authors noted that excluding older people and those with MCC is a gap during a time when U.S. populations with MCC are growing. A review of ongoing RCTs targeting 10 common chronic conditions and registered through ClinicalTrials.gov found that 79 percent excluded at least one concomitant chronic condition (Buffel du Vaure et al., 2016; McGilton et al., 2018). Furthermore, studies have shown that reporting of concomitant chronic conditions is limited (Boyd et al., 2012). Even when studies allow people with MCC to participate, the heterogeneity of the population may still not represent those living with MCC if recruitment and retention strategies are not designed to enhance participation of appropriate populations (Bowling et al., 2019; Thomas et al., 2023). Underrepresentation of participants with MCC and underreporting of comorbid conditions results in limited knowledge on how to manage the complexity of MCC and reduced ability to improve patient-oriented outcomes through evidence-based care. Analysis of Multiple Chronic Conditions Studies Traditional research tends to examine one outcome at a time, and the methodologic issues in appropriately designing and analyzing studies to understand implications for people with MCC require careful approaches (Weiss et al., 2014). Approaches to understanding heterogeneity of treatment effect are becoming more widely developed (Kent et al., 2020). Clinical Care for Individuals with Multiple Chronic Conditions Despite the increasing U.S. prevalence and impact of multimorbidity, no consensus has been reached on clinical recommendations to guide MCC treatment, which is particularly relevant in women (Regensteiner and Reusch, 2022). Including gender-specific practice guidelines when appropriate is integral for delivering personalized medical care beyond the traditional, “one-size-fits-all” approach. A shared discussion between the clinician and patient about screening, evaluation, diagnosis, and treatment should be based on genetic differences between women and men and their differing manifestations of disease and drug response. For example, the biological effects of androgen, estrogen, and progesterone on vasculature influences PREPUBLICATION COPY: UNCORRECTED PROOFS 

26 ADVANCING RESEARCH ON CHRONIC CONDITIONS IN WOMEN the incidence and response treatment for women with heart disease (Mauvais-Jarvis et al., 2020; Reue and Wiese, 2022). Sex differences reported in the innate and adaptive immune system likely influence women’s risk for certain conditions (e.g., asthma, autoimmunity) and response to vaccination and certain cancer therapies (Gubbels Bupp et al., 2018). Clinical guidelines that follow consensus statements from medical societies and systematic reviews focus on single chronic conditions and fail to include the holistic impact of MCC. Sex and gender differences in multimorbidity are understudied. This makes it difficult to translate scientific evidence into clinical practice to assist with daily decision making. Real- world registries with increased representation of women and those with MCC should be the basis for clinical guidelines to increase the validity and generalizability of research findings. Sex- specific clinical practice guidelines and assessment tools offer significant benefit to patient care. SUMMARY Research has actively prioritized the study of single diseases and single-disease models across the translational spectrum from basic science to population health. Animal models that examine the etiological mechanisms of MCC, especially for those conditions that cluster in women, are needed and should further examine the role of inflammation and aging-related mechanisms. Improvements in multimorbidity indexes that define MCC and diagnostic tools are needed for capturing MCC in women, which should include female-specific conditions to more fully understand the impact of MCC. To prioritize research on MCC, clinical and population research should include more women with MCC in clinical trials. Some evidence shows that lifestyle behaviors and other factors influence MCC; however, more research should focus on the role of early-life events from early childhood and adolescence and the reproductive stages over a woman's life-span. Research should also refine methods for studying factors related to the structural and social determinants of health and their impact on lifestyle behaviors, such as physical activity, smoking cessation, stress management, and sleep interventions, to improve quality of life and clinical outcomes in women with MCC. Much of clinical medicine is based on a single-disease approach to care, with most clinical practice guidelines focused on single conditions and limited attention for MCC (Boyd et al., 2005; Boyd and Kent, 2014; Uhlig et al., 2014). Research should assess how changes in health care service delivery to reduce fragmented care can improve MCC treatment in women. Last, research should examine the need for and development of sex-specific clinical practice guidelines to deliver personalized medical care that is beyond the traditional “one-size-fits-all” approach. To develop such guidelines, research findings should be disaggregated and analyzed according to sex and/or gender. REFERENCES Agarwal, S. D., and B. E. Landon. 2019. Patterns in outpatient benzodiazepine prescribing in the United States. JAMA Network Open 2(1):e187399. AHRQ (Agency for Healthcare Research and Quality). 2023. Advancing patient-centered care for people living with multiple chronic conditions. https://www.ahrq.gov/patient-safety/settings/long-term- care/resource/multichronic/mcc.html#:~:text=Defining%20Multiple%20Chronic%20Conditions %3A%20In%20its%20work%2C%20AHRQ,or%20more%20chronic%20physical%20or%20men tal%20health%20conditions (accessed March 13, 2024). PREPUBLICATION COPY: UNCORRECTED PROOFS 

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