Letter from the Editor, Jessica Sanders, PhD, MSPH, 2019
The University of Utah’s Center of Excellence in Women’s Health, in collaboration with the Utah Department of Health and the Utah Women’s Health Coalition, has prepared an interdisciplinary publication devoted to Women’s Health in Utah-The Utah Women’s Health Review. This review represents an overview of health situations and opportunities for improvement in community health in Utah.
The Utah Women’s Health Review is an opportunity to highlight how far we have come in the last decade, since the Women’s Health in Utah update was last published (https://uofuhealth.utah.edu/coe-womens-health/docs/coe-supplement-vol12.pdf), and also to serve as a forum for updates. This review also sheds light on gender differences and the areas where gender disparities continue to exist, and brings to light new and unresolved health concerns that need to be addressed. In this publication we have thoughtfully considered the intersection of physical and reproductive health, social health, emotional health, occupational and financial health, environmental health, intellectual health and spiritual health.
The goal of this publication is to update knowledge surrounding women’s health issues in our Utah community and beyond, as well as to create a tool that can be used to improve health for years to come and to serve as an open access home for publishing region- specific research. The Utah Women’s Health Review also serves as a model for other Academic institutions and states to bring together interdisciplinary researchers, public health practitioners and women’s health advocates to collaborate on a body of work that focuses on regional health issues.
The broad spectrum of articles highlights the reality that health is more than one dimension—and that thinking of health in these multiple dimensions more accurately portrays the women’s health challenges in public health.
Center of Excellence in Women’s Health
The Center for Excellence in Women’s Health (CoE) is a multidisciplinary group focused on enhancing overall health and wellness for women. We are founded on the 5 pillars of community outreach, clinical care, research, education and leadership development.
Our goal is to empower women of all ages with the knowledge to improve their health and the health of their families. The work of the CoE is based on:
•Respect, caring, compassion, and integrity
•Being non-competitive, non-hierarchical, and collaborative
We are supported in part by the Department of Obstetrics and Gynecology, the Office of the Vice President for Health Sciences, the Center for Clinical and Translational Science, the Office of Health Equity and Inclusion, DHHS Office on Women’s Health, and the Office of Research on Women’s Health. This review has been made possible in part by the Educational Resource Development Council at the University of Utah.
The 7 Domains of Women’s Health
Everything we do is based on our philosophy that health is not just physical health, but also encompasses psychological/emotional, environmental, sociocultural, intellectual, economic, and spiritual – an approach we sum up as “The 7 Domains of Health”. We promote these domains through information, research, education, outreach programs and clinical care. The COE provides a great opportunity for people with a wide range of philosophies to network and share and develop innovative projects together.
Rural-Urban Disparities in Health Outcomes and Access to Care among Women in Utah
Objectives: The aim of this research project is to enhance understanding of the current rural-urban disparities in health outcomes among women in Utah.
Methods: Percentages, confidence intervals and standard errors for fifteen health outcomes were calculated using age-adjusted data from the Utah Behavioral Risk Factor Surveillance System in order to compare rates for women in 63 rural, urban and frontier areas.
Results: Women in rural areas had lower (better) percentages in all eight of the outcomes relating to general physical and mental health, as well as chronic conditions. Women in rural areas had higher (worse) percentages in all seven of the outcomes representing access to care and preventive services. Frontier areas had higher (worse) percentages than both rural and urban areas in eleven of the fifteen outcomes; five of them were significantly higher.
Conclusion: Women in frontier areas in Utah have considerable challenges with both access to health care and preventive services, as well as general physical and mental health and chronic conditions. Women living in rural areas continue to struggle with access to care and preventive services, but have lower rates than urban areas in terms of a number of outcomes.
The purpose of this research is to examine the rural-urban disparities in health outcomes among women in Utah. Urban, rural and frontier areas are considered in our analysis. Urban areas are classified as having a population of over one hundred people per square mile and make up only 5% of the land area in the State, although they contain approximately 75.5% of the total population. Rural areas are classified as having a population of six to ninety-nine people per square mile, make up 40% of the land area in the state of Utah and contain 21% of the population. Frontier areas have fewer than six people per square mile and cover 55% of the state but only contain 3.5% of the total population. A majority, 801,081 (80%), of women 18 and older reside in urban counties in Utah, while the remaining 206,426 women (20%) reside in the rural and frontier counties.
Health disparities are defined as the differences in care experienced by one population compared to another population (Agency for Healthcare Research and Quality, 2010). The reason disparities exist among populations are complex and may affect access, quality of care and outcomes (Egede & Bosworth, 2008; Institute of Medicine, 2002).
Comparisons between health outcomes and disparities among different genders, races, ethnicities, and socioeconomic situations are common in health assessments; however, disparities by geographic regions may also exist.
Poverty and access to care are two of the main reasons that disparities exist between women in rural and urban areas. Level of education, transportation challenges and adequate health insurance are also contributing factors. Lack of financial stability negatively affects access to health services and decreases health status. People who live in poverty often have a higher incidence of chronic diseases, including mental illnesses such as depression and anxiety. (Brown, 2015)
Understanding the disparities that women face is extremely important to society at large because poor health in women often translates into poor health for families, as women are often the ones responsible for meeting the physical and emotional needs of family members (Cawthorne, 2008). In particular, obstetrics providers are in short supply in rural areas, and that lack of access has been linked with poorer health outcomes (Nesbitt et al., 1997). Due to the lack of supply of obstetrics providers, women in rural areas often rely upon family medicine physicians to provide this care (Cohen & Coco, 2009). Access to care in general has been linked with socioeconomic status (Dunlop et al., 2000) and geographic location (Glazier et al., 2004). Aday and Andersen argued that actual use of health services was determined by individual health needs, the predisposition to seek care, and a range of enabling or impeding factors (Aday & Andersen, 1974; Andersen, 1995). It has also been recognized that women live within complex and diverse social, economic, and environmental circumstances that influence options for health behavior and health care (Hankivsky & Christoffersen, 2008; Hankivsky et al., 2010).
Disparities in health outcomes among women exist between racial and ethnic groups as well. Women of color fare worse than white women across a broad range of measures in almost every state, and in some states these disparities are quite stark (James et al., 2009). Preventive services such as breast cancer screening are lower in rural areas, and the result is that breast cancer in rural women is often diagnosed at a later stage compared to diagnoses in urban women (Rayman and Edwards, 2010). Lower screening rates may be attributable to lack of insurance, geographic maldistribution of screening facilities, and poor health literacy. Rural women are also less likely to receive preventive health screenings than urban women (Hageman et al., 2010). Disparities in mental health services have resulted in rural residents being far less likely than urban residents to receive mental health treatment (Hoge et al., 2007). A variety of barriers keeps people from seeking and receiving mental health care, including the cost of treatment, lack of awareness of mental illness, not believing that treatment is necessary, lack of time, not knowing where to go for services, and stigma surrounding mental illness (Mulder, 2012). Some of these barriers are amplified in rural and frontier communities due to the lack of anonymity in these communities (New Freedom Commission on Mental Health, 2004). The distance and time needed to access services, and the fact that rural residents are more likely to be uninsured and poorer than their urban counterparts, contribute to this disparity (Ziller et al., 2003). Conversely, some aspects of living in rural areas may help protect women’s mental health. One study showed that women living on farms scored higher than average on mental health assessments (Hillemeier, 2008).
This analysis of the health outcomes among women in rural, urban and frontier areas in Utah addresses many of these disparities and the barriers that contribute to them. It also considers chronic conditions as well as access to care and preventive services and the impact of household income on each of these factors.
The Utah IBIS-PH Query System (Indicator-Based Information System for Public Health Data Resource) was used to evaluate age-adjusted aggregate data of small health areas from the Utah Behavioral Risk Factor Surveillance System (BRFSS) for fifteen different health outcomes. Data for 13 of the health outcomes that we analyzed were from 2012-2014. Cigarette smoking and physical inactivity data were from 2009 – 2014 due to the small number of survey responses in some areas. Age-adjusted rates, confidence intervals and standard errors for all fifteen health outcomes were calculated in order to compare rates for women in 63 urban, rural and frontier “small health areas.” Each small area contains a population ranging from approximately 20,000 to 60,000 persons. These geographic areas are particularly useful for public health assessment in Utah since the designation of each small area is based on specific criteria including population size, political boundaries of cities and towns, and economic similarity.
In Utah, urban areas are classified as having more than one hundred people per square mile, rural areas are classified as having six to ninety-nine people per square mile, and frontier areas are The Utah Women’s health Review 7 classified as having < 6 people per square mile. Since frontier areas typically are left out of health research, all three classifications are considered. We made the assumption that disparities would exist between rural and frontier areas, just as they do for rural versus urban areas. Seven of the outcomes address access to care and preventive services, while eight of the outcomes represent general physical and mental health including chronic conditions.
Age-adjusted rates are a weighted average, with each age-specific rate weighted by the proportion of people in that age group in the U.S. 2000 standard population. Age-adjusted rates control for age effects and allow for better comparability of rates across areas. These rates may also be used to control for age effects when making comparisons across several years of data, as the age distribution of the population changes over time.
Confidence intervals were calculated for each of the health outcomes using the Utah IBIS-PH Query System. In this system the confidence factors are obtained by using SAS ® software that requires specification of the percentage of the inverse gamma distribution to be excluded on either end of the distribution (2.5% for a 95% confidence interval), and the two parameters are associated with the distribution function: the mean and the variance. For this reason, it can be assumed that confidence intervals that do not overlap are highly likely to be considered statistically significant. Specific definitions of each health outcome used in the analysis are listed in Table 1.
Adjusted linear regression was run using STATA ® on each health outcome separately, in order to determine the association with household income (scaled per $10,000). Poverty data were obtained from the Utah IBIS-PH Query System BRFSS data for 2015. This analysis is important since the lack of financial stability negatively affects both access to care and health status. People who live in poverty often suffer from higher rates of chronic disease and mental illness. Results of the adjusted linear regression are listed in Table 3.
The results of the analysis document compelling evidence of the persistence of health disparities between urban, rural and frontier areas in Utah. Women in rural areas have lower (better) percentages in all eight of the outcomes relating to general physical, mental and chronic conditions. Conversely, women in rural areas have higher (worse) percentages in all seven of the outcomes representing access to care and preventive services. The only outcome that was statistically significantly lower in rural areas was obesity.
Depression and obesity percentages were both statistically significantly higher for urban areas than rural areas. Frontier areas had the highest percentages in eleven of the fifteen outcomes, and five of these differences were statistically significant. These five areas include routine medical checkup, daily fruit consumption, smoking, mammography screening and physical inactivity. Table 2 contains the percentages, confidence intervals and standard errors for each health outcome in rural, urban and frontier areas.
Frontier areas had the lowest percentages for cost as a barrier to care and having no personal doctor. This seems to suggest that even though women living in frontier areas do not have as many routine medical checkups or mammography screenings, they are more likely to have a personal doctor and they do not consider cost as a barrier to care as often as women in rural and urban areas might. The percent of women who have had no mammography screening in the past two years or never was highest in frontier areas (40.4%) followed by rural (33.8%) and urban (33.5%). Figure 1 is a map of the percent of women over age 40 who have not had a mammogram in the last 2 years or never.
The percent of women who have not had a regular medical checkup in the past twelve months was also highest in frontier areas (41.1%) followed by rural (38.4%) and urban areas (37.4%). Figure 2 shows the percent of women who have not had a routine medical checkup in the past twelve months.
The percentage of women with poor mental health was highest in frontier areas (21.3%) followed by urban (19.4%) and rural (18.6%). On the other hand, depression was lowest in rural areas (25%) followed by frontier areas (26.9%) and then urban areas (27.9%).
The percentages of obesity, diabetes, cancer and asthma were higher in urban areas than in rural areas. Obesity, diabetes and cancer percentages were the highest in frontier areas but none of them are statistically significantly higher. The percentage of women who use cigarettes was the highest in frontier areas (12.1%), followed by rural areas (9.2%) and then urban areas (8.8%). The percentage of women who use cigarettes in frontier areas was so much higher than in rural areas that the difference was statistically significant.
The highest percentage of women with asthma was in urban areas (11.1%), followed by frontier (10.4%) and then rural (9.7%). The higher percentage of women with asthma in the frontier areas than rural areas may be linked to occupational and environmental conditions such as dust and agriculture. One of the unexpected findings of the analysis revealed that five of the “small areas” were frequently ranked in the top five unhealthiest small areas in the state in each outcome analyzed. These five areas are all located in the Salt Lake Valley and include Magna, Glendale, West Valley (East), Kearns, and Midvale. Figure 3 is a map of the Salt Lake Valley and shows the locations of the five small areas that were most frequently in the top five unhealthiest areas for each health outcome. Magna is in the top five unhealthiest areas in 10 of the 15 outcomes, compared to Glendale (8), West Valley (East) (7), Midvale (6) and Kearns (6). These areas should be of particular concern due to the high number of poor outcomes facing women in these areas.
Adjusted linear regression was performed on each health outcome with household income, and the results are listed in Table 3. All of the health outcomes show statistically significant negative associations with household income except for cancer (P=0.469). Routine dental care had the highest beta value (-3.21) followed by general health status (-2.16), physical inactivity (-1.90), fruit consumption (-1.86) and no personal doctor (-1.85). The smallest beta values were cancer (-0.11), asthma (-0.63), diabetes (-0.71), no routine medical checkup (-0.77) and mental health (-1.15). These values can be viewed as indicators of the strength of the association that household income has on these health outcomes.
The five areas that were most often included in the top five healthiest areas in Utah for each health outcome are Cottonwood Heights, Sandy (SE), SLC (Foothill/U of U), Orem (East), and Farmington/Centerville. All are located in the 1st quartile of household income, suggesting a strong association between good health and high income. Conversely, the five areas that were most often in the top five unhealthiest areas in Utah for each health outcome are Magna, Glendale, West Valley (East), Midvale, and Kearns; these areas are spread out between the 2nd, 3rd, and 4th quartiles. This finding suggests that poor health is also associated with lower income, but not as strongly as good health is with higher income. The variance may be due to environmental factors, race/ethnicity and culture, educational level, physical activity, and individual- and neighborhood-level social and behavioral factors. Discussion/Implications
This study demonstrates that health disparities exist between women in urban, rural and frontier areas throughout Utah. The type and extent of disparity differ for each of the three demographic areas we examined. The greatest disparities exist in the frontier areas, where five out of the fifteen health outcomes examined are statistically significantly worse than in urban as well as rural areas. Moreover, five areas in the Salt Lake Valley have particularly high percentages of obesity, fair/ poor general health, diabetes, physical inactivity and no routine dental care. The counties that make up the TriCounty Local Health Department are classified as rural areas and had particularly high percentages of smoking, no routine medical checkup, fewer than two servings of fruit per day and no mammogram in the last two years for women over age 40. Frontier areas facing particular challenges with poor health outcomes include Carbon/Emery Counties (smoking and cancer), Grand/San Juan Counties (routine medical checkup, no personal doctor, no mammogram) and Juab/Millard/Sanpete Counties (no routine medical checkup and no mammogram).
Among the six highest percentage areas in Utah for having no routine medical checkup in the past twelve months, two are frontier (Grand/San Juan Counties and Juab/Millard/Sanpete Counties) and two are rural (TriCounty LHD and Utah County (South), while the two urban areas are Lehi/Cedar Valley and Provo (South).
The evidence that frontier and rural areas continue to struggle with access to care and preventive services is perhaps the most important aspect of this paper. Women living in frontier areas such as Grand, San Juan, Juab, Millard and Sanpete Counties have particularly high percentages of having no routine medical checkup in the past 12 months (45.5% – 49%) and no mammography screening in the last two years or never (46.44% – 60.88%).
The five areas with the highest percentage for having no leisure time physical activity were Magna, Rose Park, Glendale, Kearns and West Valley (East), four of which (Rose Park being excluded) are in the top five most unhealthy areas overall. This brings out a discussion point regarding access to physical activity opportunities in these areas, including walking/biking trails, gyms, parks, open space and outdoor recreation locations. The five areas with the lowest percentages of physical inactivity (Orem (east), SLC (Foothill/U of U), SLC (Avenues), Holladay and Cottonwood Heights) are all located along the foothills of the Wasatch Front and appear to have good access to trails, parks, gyms and open space, although a more in-depth analysis of this statement should be considered for future research.
We recommend further analysis regarding access to care and preventive services for women in frontier and rural areas. The Federal National Health Service Corps (NHSC) Loan Repayment, Scholarship, and NURSE Corps programs are critical for addressing the healthcare workforce shortage, in particular in rural areas. Currently there are 134 healthcare providers in Utah who are affiliated with the NHSC programs. The State of Utah also has a number of programs aimed at addressing healthcare workforce shortages. These programs are the State Primary Care Grants (SPCG), Rural Physician Loan Repayment Program (RPLRP), and the Healthcare Workforce Financial Assistance Program (HWFAP). The combined effect of both Federal and State programs supply 127 healthcare providers to frontier and rural areas (58 frontier and 69 rural). These programs exist to offer financial and other support to primary care providers and healthcare facilities in medically underserved communities throughout Utah.
In conclusion, women living in frontier areas in Utah have significantly higher percentages of having no routine medical checkup in the past twelve months, consume fewer than two servings of fruit per day, currently smoke cigarettes, have not had a mammogram in the past two years (if ever), and participate in no leisure time physical activity. On the other hand, women living in urban areas have significantly higher percentages of depression and obesity than women in rural areas. These disparities, which are likely to be caused by multiple factors, highlight some of the primary issues facing access to healthcare and health outcomes among women in Utah.
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Nearly half of Americans are diagnosed with periodontal disease, of whom an estimated 40% suffer from moderate to severe periodontitis.(Eke et al., 2012) Periodontal disease is a broad term for conditions that cause inflammation and destruction of the gums and the structures surrounding the teeth, such as gingivitis and periodontitis.(Jared & Boggess, 2008) Periodontal diseases are caused by the invasion of bacteria from plaque. Periodontal disease has been associated with a host of adverse health outcomes including heart disease, increased risk for dementia, respiratory problems, and diabetes.(US Department of Health and Human Services, 2000)
Although periodontal diseases affect the adult population as a whole, pregnant women are especially vulnerable to oral health problems due to hormonal changes that occur in the body during pregnancy.( Wu, Chen, & Jiang, 2015) It has been shown that around 40% of women will develop new oral health problems during their pregnancies.(Jared & Boggess, 2008) Poor oral health during pregnancy has been associated with adverse birth outcomes, including preeclampsia, low birth weight, and preterm birth.(Jared & Boggess, 2008) Several researchers have hypothesized that inflammation in the mouth, such as gingivitis or periodontitis, may trigger an inflammatory response that may be the mechanism for various adverse pregnancy outcomes.(Wu et al., 2015) Some researchers have hypothesized that receiving dental care prior to conception may be more effective than receiving dental care during pregnancy in preventing adverse birth outcomes. (Boggess et al., 2005) In Utah, a study conducted using Pregnancy Risk Assessment Monitoring System (PRAMS) data found that individuals who did not receive a teeth cleaning in the 12 months prior to pregnancy had an increased prevalence of low birth weight babies.(Author, 2017, June 20)
Given the evidence to date regarding the link between poor preconception and pregnancy oral health and adverse pregnancy outcomes, it is critical that women have access to dental care resources, not only during pregnancy but also prior to pregnancy. Currently, Medicaid only covers dental care for pregnant women. While many women receive dental care during pregnancy, receiving care during this time period may be too late to prevent adverse pregnancy outcomes. Periodontitis and other oral hygiene issues are highly preventable. More comprehensive dental health care is needed, specifically for individuals with Medicaid or lack of insurance. Providing more comprehensive care and educating women about the importance of dental care throughout their reproductive years could potentially improve adverse birth outcomes. By educating and emphasizing lifetime dental care, these negative birth outcomes, as well as other adverse health outcomes due to oral health, could be easily and inexpensively prevented or resolved.
Utahns are accessing dental care at a higher rate than the national average. Based on a self-report survey conducted by the Centers for Disease Control (CDC), 74% of Utahns reported they had received a dental exam compared to the national average of 70%, Additionally, women in Utah are better at receiving dental exams than males: 75% of females received a dental exam within the past year, compared to 71% of males. Although Utahns are doing better compared to the national average, approximately of 25% individuals in the state are not receiving annual dental exams. Based on the Behavioral Risk Factor Surveillance System and when observing access by race, Latinos, who make up 13.7% of Utah’s population, have the highest rates of non-compliance, with just over half (58%) of this population receiving a dental exam in the last year.
When considering the unique needs of reproductive- age women, the PRAMS data in Utah has recently started tracking dental behaviors among this demographic. According to the PRAMS survey from 2012-2013 (see Figure 1), 63% of women received dental care prior to pregnancy and 55% received dental care during pregnancy. While 91% of women said that they thought it was important to care for their teeth, this did not always translate into actually receiving care. One factor that encouraged women to receive a dental exam was if a healthcare provider told them that they should go to the dentist, although it is unclear if individuals were told about dental care during their dental visit or at a different time. Of those women who talked to a provider about the importance of oral health during pregnancy, 77% received a teeth cleaning. Of those who were not directly told by a provider that oral health care was important, only 23% received this oral care during pregnancy. According to the PRAMS data, based on ethnicity, 42% of Hispanic women said that they had received a dental cleaning in the 12 months prior to pregnancy and 37% said they received a dental cleaning during pregnancy. Non-Hispanic women had higher rates, with 66% of women receiving a dental cleaning before pregnancy and 59% receiving this oral care during pregnancy. There are distinct differences between individuals who had received a teeth cleaning within a year and those who had not. Women who were not Hispanic, had a higher socioeconomic status, and had dental insurance received dental care both prior to and during pregnancy at a higher rate than individuals without these characteristics. These differences point to a potential
A vital factor in evaluating oral health care is having dental insurance. Nationwide, 66% of the population has insurance for dental health care. (National Association of Dental Plans, 2016) Of those with insurance, 32% of individuals receive it through public programs, such as Medicaid and Medicare. This number has increased from what it was in 2013. Based on the Utah PRAMS data from 2012-2013, among reproductive-aged women, 68.93% have dental insurance.
7 Domains of Health
Dental health is an integral part of a healthy lifestyle, primarily intersecting with the physical, financial, and environmental domains of health. Physically, individuals who do not receive regular dental care have an increased risk for multiple adverse health conditions.(US Department of Health and Human Services, 2000) Reproductive-aged women potentially have an increased risk for adverse birth outcomes and infertility.(US Department of Health and Human Services, 2000) Financially, many people feel that they cannot afford dental care. One study found that one out of five individuals were not able to afford dental care. (Brown, Finlayson, Fulton, & Jahedi, 2009) Even among those with insurance, around 41% of individuals pay out of pocket for dental care.(Wall & Guay, 2016) This serves as a significant barrier for many individuals because, in many circumstances, dental care is lower than other needs on the financial priority list.
Environmentally, lack of access is a common problem, specifically for low-income individuals and those on Medicaid. Many dentists either will not see Medicaid patients or have limited openings for new patients. A 2012 survey conducted by the Utah Medical Education Council found that 150 of the 1,006 (15%) practicing dentists in Utah treat Medicaid patients. Additionally, much of Utah is considered a Health Professional Shortage Area (HPSA) (Figure 2), which considers the provider- to-patient ratio, poverty level in the area, water fluoridation, and travel time needed to access care. Although Utah has a similar distribution of dentists as the United States, with 67 dentists per 100,000 individuals, (US Department of Health and Human Services, 2015) rural individuals often have lower accessibility, as seen in Figure 2.
Resources and Recommendations
Nationally, interventions have traditionally been aimed at improving dental care in children. Regular dental care is provided for children on Medicaid or on Utah’s Children’s Health Insurance Program (CHIP). In addition, the Utah Oral Health Program aims to promote use of fluoride and sealants, prevent tooth decay in children, and encourage dental visits for children and adults. As seen in the PRAMS data, in order to encourage dental visits, it may be useful to utilize primary care providers for suggesting and encouraging an annual dental exam. As previously mentioned, affordability and coverage are large barriers to receiving dental care. Aside from pregnant women, Medicaid only includes emergency dental coverage for adults in Utah. Through expanding dental coverage to include annual exams and preventative care for Utah adults on Medicaid, health outcomes may improve. In addition to expanding coverage, dentists could be provided with financial incentives to treat low-income and Medicaid patients. Lastly, health literacy programs could be developed in order to educate individuals about the importance of good dental care in relation to overall physical health as well as oral health. Since many individuals do not understand the importance of dental care in relation to adverse health outcomes, education may motivate them to receive an annual exam. Women are often the gateway to a family’s health, so by encouraging and empowering women to receive annual exams and maintain good oral health, providers and health care workers may be able to impact entire families.
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Brown, T. T., Finlayson, T. L., Fulton, B. D., & Jahedi, S. (2009). The demand for dental care and financial barriers in accessing care among adults in California. J Calif Dent Assoc, 37(8), 539-547. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/19753880
Eke, P. I., Dye, B. A., Wei, L., Thornton-Evans, G. O., Genco, R. J., & CDC Disease Surveillance work group: James Beck (University of North Carolina, C. H., U. S. A.), Gordon Douglass (Past President, American Academy of Periodontology), R.y Page (University of Washin. (2012). Prevalence of periodontitis in adults in the United States: 2009 and 2010. J Dent Res, 91(10), 914-920. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/22935673
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Wall, T., & Guay, A. (2016). The per-patient cost of dental care, 2013: a look under the hood. In. Health Policy Institute Research Brief. American Dental Association. Retrieved from http://www.ada.org/~/media/ADA/Science%20and%20Research/HPI/Files/HPIBrief_0316_4.pdf Author[Abstract]. 2017, June 20-23.
Wu, M., Chen, S. W., & Jiang, S. Y. (2015). Relationship between gingival inflammation and pregnancy. Mediators Inflamm, 2015, 623427. Retrieved from https://www.hindawi.com/journals/mi/2015/623427/
Willis SK, Simonsen SE, Stanford JS, Schliep K. (2019). Dental Health Among Pregnant Utah Women. Utah Women’s Health Review. doi: 10.26054/0KHGEHC344.
Intergenerational Poverty, Women & Children’s Health
Background: Utah’s Intergenerational Poverty Initiative and Public Health
Poverty is a key driver of poor population health outcomes. Families or individuals in poverty are more likely to experience chronic conditions, including asthma and diabetes, less likely to have access to healthy food and walkable neighborhoods, and more likely to have limited access to medical care. Women are at an even greater risk of poverty, due to social conditions. Because health is largely patterned along socioeconomic lines, eliminating or reducing poverty would lead to dramatically im-proved public health 1. In 2012, the State of Utah embarked on a major initiative to address poverty, passing the Intergenerational Poverty Mitigation Act to target families experiencing poverty in multiple generations. This Act is premised on the idea that not all poverty is the same. Some families experience ‘situational’ poverty, receiving public assistance for less than 12 months. For families in situational poverty, the public assistance system helps families move out of poverty. The State distinguishes a second group, those in ‘entrenched’ or cyclical poverty. “Intergenerational Poverty is poverty in which two or more successive generations of family continue in the cycle of poverty, as measured through utilization of public assistance at least 12 months as an adult and at least 12 months as a child.” -Utah Intergenerational Welfare Reform Commission, 2016 Report 2. The Intergenerational Poverty Mitigation Act’s goal is to reduce the number of families caught in intergenerational poverty (IGP). The IGP Act andsubsequent IGP Initiative coordinates data across state public assistance agencies to better understand IGP families and develop programs and policy recommendations for Utah going forward.
Defining IGP Adults and Children
The focus of the IGP Mitigation Act is children, but the Act recognizes that to address the needs of children, programs and resources must also help parents. The IGP Mitigation Act identifies cohorts of IGP parents and children to target programs and data tracking: 1) IGP parents are defined as parents who received public assistance as a child; 2) IGP children are children whose parents received public assistance as a child; 3) non-IGP or ‘at-risk’ children are children who are currently on public assistance but whose parents either did not receive assistance, or there is no record of them receiving assistance. The different cohorts are based on public assistance usage data beginning in 1989 (when usage data became available). Finally, several groups are not included in the IGP definitions and categories, which has implications for the data collection and subsequent programs and policy recommendations. Adults who grew up outside of Utah and adults who are non-citizens are not included in the definition of IGP adults. Therefore immigrants are largely excluded from IGP analysis, except in the at-risk child cohort. In addition, Native American families who received public assistance through tribal-based safety net programs were also excluded. Because of these definitions, it is estimated that the number of individuals experiencing poverty across generations is higher than the state’s count 3.
Utah Data Trends and Indicators: Intergenerational Poverty, Women and Children
Women experience higher levels of intergenerational poverty. Of the IGP adults, 68% are women. This is consistent with poverty across Utah, where women experience higher poverty rates than men. In Utah, 12.2% of women are living in poverty, lower than the U.S. average of 16% 4. While Utah’s rate of poverty is lower than the national average, the poverty rates look very different when disaggregated by race and ethnicity. Women of color are more likely to live in poverty than White women and their male counterparts. According to Census data, in Utah Latina or Hispanic women have a poverty rate of 25.9%, Black women have a poverty rate of 20.3%, and American Indian women have a poverty rate of 36.1%. Rural women also have higher poverty rates than urban women in Utah. Several rural counties in Utah have some of the highest rates of intergenerational poverty 5. Single, female-headed households are at the greatest risk of being in poverty among IGP and non-IGP women. Overall, in Utah, 28.9% of female headed households are in poverty. Women with younger children have even higher rates of poverty; among female-headed households with children under the age of 18, 37.5% are in poverty; among female-headed households with children under the age 5, 46.9% are in poverty 6. For children, the child poverty rate has declined slightly in Utah to 13%, compared to a national average of 21%. Similar to women in poverty, children of color and rural children experience higher rates of poverty in Utah 7.
Women and Children’s Health
Utah’s IGP initiative reveals several trends regarding poverty, women and children’s health. In some areas, IGP women reflect the same trends seen among non-IGP women in poverty; in other areas, these two groups diverge. Among IGP women and children, enrollment in public health coverage is higher than the non-IGP population. This is not surprising given that the IGP Act defines intergenerational poverty as public assistance usage. Medical assistance is one of the main types of public assistance used by the IGP cohort, following SNAP or food stamps. In Utah 12% of parents do not have health coverage, which is consistent with the national average. For children, Utah has one of the highest rates of uninsured children in the nation, despite making progress in recent years. 7% of Utah children lack health insurance, compared to 5% nationally. Uninsured rates for children living in poverty are even higher 8. Health care utilization is higher among the IGP population. 81% of IGP individuals had access to medical care compared to 78% of non-IGP individuals, defined as utilizing medical services at least once in the last year. IGP women also have higher rates of prenatal care, compared to non-IGP women. Among new mothers, 5% of IGP children were born to teen mothers. Overall, the teen birth rate continues to decline nationwide and in Utah. In 2014, Utah was at a teen birth rate of 7.57, and in 2015 the rate is 6.94 9.
Intergenerational Poverty and the 7 Domains of Health
Intergenerational poverty affects all aspects of physical and reproductive health, social health, emotional health, occupational and financial health, environmental health, intellectual health and spiritual health. Intergenerational poverty underscores how different social conditions and factors affect health outcomes and well-being. IGP children are at a greater risk for experiencing adverse childhood experiences (ACEs), which can affect their entire life course. Children who grow up in poverty are more likely to experience ACEs or poverty-induced trauma and stressors. Poverty-induced trauma can impact a child’s healthy brain development and increase the likelihood of developmental delays, chronic health problems and poor physical health outcomes later in life 10. IGP children have higher rates of chronic school absenteeism, creating barriers to achieving optimal intellectual, occupational and financial health. Moreover, families in poverty often live in worse environmental conditions, such as apartment buildings with poor indoor air quality, or homes closer to industrial sites and pollutants. Poverty also imposes barriers to emotional and spiritual health; IGP families and children have more mental health diagnoses than the non-IGP cohort 11. The IGP Initiative in Utah illustrates that there is not one single issue area for intervention. The impact of entrenched poverty on individuals and children affects all 7 domains of health.
The IGP initiative outlines many promising programs and policies to improve families’ health outcomes and reduce poverty. In recent years, lawmakers have adopted several state policies specifically targeting children in the IGP cohort, including expanding access to high quality pre-school for IGP children. Promising policies in the future should target parents and their children: access to medical care, increasing working family tax credits, and expanding evidence-based home visiting programs. Policies that would expand access to Medicaid coverage for parents, including family planning services and behavioral health care, would be an effective measure to support IGP parents. Not only would parents greatly benefit from expanded access to care, but when parents have health insurance they are more likely to make sure their children are connected with care and coverage. A state earned income tax credit or EITC is another important measure, providing a tax credit to low-income working families. Finally, expanding home visiting programs allow more mothers and children to receive support and care during pregnancy and the first years of a child’s life. Home visiting programs are evidence-based and show improved outcomes for mothers and infants. Overall, programs that support both parents and children provide families with a stronger foundation for moving out of poverty.
Utah’s Intergenerational Poverty Commission produces a thorough annual report on the state of intergenerational poverty in Utah. The IGP initiative’s comprehensive data collection and sharing across public agencies has been a model for other state initiatives. The annual report gives detailed information about improvements and setbacks in Utah’s efforts to reduce intergenerational poverty.
Utah Intergenerational Welfare Reform Commission. (2016). Utah’s Fifth Annual report on Intergenerational Poverty, Welfare Dependency and the Use of Public Assistance. Accessed 12/14/2019 at https://jobs.utah.gov/edo/intergenerational/igp16.pdf
Madsen, Susan R. (2016). Utah Women Stats Research Snapshot: Poverty Among Utah Women. Utah Women & Leadership Project, No. 2. Accessed 12/14/2019 at https://www.uvu.edu/uwlp/docs/uws_poverty.pdf
Annie E. Casey Foundation. (2019). Kids Count Data Center. Accessed 12/14/2019 at http://datacenter.kidscount.org/data#UT/2/0/char/0
Utah Intergenerational Welfare Reform Commission. (2016). Utah’s Fifth Annual report on Intergenerational Poverty, Welfare Dependency and the Use of Public Assistance. Accessed 12/14/2019 at https://jobs.utah.gov/edo/intergenerational/igp16.pdf
School Readiness Matters: The Campaign for Grade Level Reading: http://gradelevelreading .net/wp-content/uploads/2014/06/School-Readiness-Matters-Research-Confirms-and-Citations-r2_KC.pdf
Utah Intergenerational Welfare Reform Commission. (2016). Utah’s Fifth Annual report on Intergenerational Poverty, Welfare Dependency and the Use of Public Assistance. Accessed 12/14/2019 at https://jobs.utah.gov/edo/intergenerational/igp16.pdf
Mandle J. (2019). Intergenerational Poverty, Women & Children’s Health. Utah Women’s Health Review. doi: 10.26054/0KXJHKY9X7.
The Impact of Living at Altitude on Depression and Anti-depressant Function in Utah Women: The Need for Novel Antidepressants
Objectives: Utah has the highest rates of depression and suicide in the US, despite high rates of antidepressant prescriptions. People living at altitude are exposed to chronic hypobaric hypoxia, which may disrupt brain serotonin and bioenergetic function, to worsen depression and reduce selective serotonin reuptake inhibitor (SSRI) function. We therefore (1) used an animal model to study altitude-related depression, and (2) evaluated novel therapeutics in depressed Utah women.
Methods: We examined depression and SSRI function in rats housed at altitude. In treatment-resistant women, we tested antidepressant potential of compounds which correct hypoxia-induced brain deficits: creatine monohydrate (CrM) for bioenergetics or 5-hydroxytryptophan (5HTP) for serotonin deficit.
Results: At altitude, female rats exhibit increased depression and lack of antidepressant response to SSRIs (except sertraline). In treatment-resistant women, adjunctive CrM and 5HTP+CrM improves depression status and bioenergetic function.
Conclusions: With significantly lower basal brain serotonin levels than men, women are likely more susceptible to altitude-related depression. Targeted treatment may be required: sertraline, CrM or 5HT-P+CrM show promise in improving mood and reducing suicidal ideation in women living at altitude or with hypoxic diseases.
Major depressive disorder (MDD) affects over 16.5% of the US population, with lifetime prevalence of up to 12% in men and 25% in women (Trivedi, 2008). Depression affects women more severely than men, potentially due to several biological and psychosocial mechanisms (Dalla, 2010). MDD is linked to poor serotonergic neurotransmission, and healthy women exhibit 52% lower rates of brain serotonin synthesis than men (Nishizawa, 1997), reduced serotonin receptor binding and higher excretion of serotonin metabolites (Dalla, 2010). Poor basal serotonin transmission may contribute to greater vulnerability to MDD in women.
Living at altitude may be linked to a brain serotonin deficit. Rats exposed to extremes of altitude (1-14 days, 20,000-25,000 ft) show reduced brain serotonin levels (Kumar, 2011). Serotonin is synthesized in two steps: the rate-limiting first step requires tryptophan hydroxylase 2 (TPH2) and molecular oxygen to convert tryptophan to 5-hydroxytryptophan (5HTP). 5HTP is then converted to serotonin in an oxygen-independent second step. Chronic hypobaric hypoxia decreases TPH2 activity, lowering levels of brain 5HTP and serotonin. Hypoxia may also compromise efficacy of selective serotonin reuptake inhibitors (SSRIs), the most widely prescribed of antidepressants (Preskorn, 1996). SSRIs improve depression status by blocking the serotonin transporter to increase synaptic serotonin concentrations. However, in animal models of low brain serotonin, SSRIs can lose antidepressant efficacy (Durkin, 2008; Kulikov, 2011). By reducing brain serotonin, hypobaric hypoxia may thus simultaneously impair depression status and exacerbate SSRI-treatment resistance.
Living at altitude is also linked to brain hypometabolism. 1Hydrogen or 31Phosphorus-magnetic resonance spectroscopy (1H-MRS or 31P-MRS) scans allow in vivo measurement of brain bio-markers for cellular energy production (Kondo, 2011a). 1H-MRS neuroimaging of age- and gender-matched healthy residents living at moderate altitude (4,500 ft, Salt Lake City, UT) vs. those at sea level (Belmont, MA or Charleston, SC) identified a deficit in forebrain levels of the bioenergetic marker creatine (Cr) in those at altitude (Renshaw, 2012). A similar deficit in forebrain Cr was found in female rats after housing at an altitude of 10,000 ft for a week, implying that hypobaric hypoxia can induce this deficit (Bogdanova 2014). Cr plays an important role in regulating energy metabolism, and low Cr is representative of cellular hypometabolism (Kondo, 2011a). A bioenergetic deficit is similarly seen in key depression-linked brain regions in MDD patients, which improves with effective treatment, but remains unchanged in non-responders (Iosifescu 2008). Living at altitude could thus increase vulnerability to MDD by causing brain deficits in serotonin and Cr levels.
Utah is representative of a high altitude state with significant burden of depression and suicidal behavior. Between 2000-2006, Utah exhibited the highest antidepressant prescription rates in the US: 18.4% vs. the US average of 10.8% (Cox, 2008). In Utah, 68% of antidepressants are prescribed for women, and >80% are for SSRIs (Gaskill, 2010). Despite this, Utah showed the highest depression index in the US in 2007, based on four criteria: annual percentage of adults and adolescents reporting a major depressive episode, adults reporting serious psychological distress, and rates of suicide (Mark, 2007). Over 30-40% of MDD patients taking anti-depressants do not respond adequately to treatment (Al-Harbi, 2012; Trivedi 2008), and treatment-resistance leads to unresolved depression, and increases suicidal ideation and suicide attempts. The Rocky Mountain States exhibit by far the highest rates of suicidal ideation (5.2% vs. 3.7%, CDC, 2011) and completed suicide (17.7 vs. 11.3 per 100,000) (Mark, 2007) in the US. Of particular relevance, the State of Utah had the highest annual prevalence of suicidal ideation in 2008-2009 (6.8%) – a rate that, incredibly, is more than three times that of Georgia, the US state with the lowest prevalence (2.1%) (CDC, 2011).
Moreover, Utah women contend with significantly greater burden of suicidal thoughts than men: 8.1% vs 5.6%, vs. the US average of 3.8% (women) vs. 3.5% (men) (CDC, 2011). Similarly, high rates of suicidal ideation are noted in women in the high-altitude States of Idaho (7%), Nevada (9%) and New Mexico (6%). Suicidal risk factors include cultural and socioeconomic factors (eg., poverty, rural residence, population density) as well as biological ones (eg., age, sex, mental illness), but depression is almost always observed in those who think about and attempt suicide. The poor quality of life inherent in 8% of Utah women expressing suicidal thoughts suggests a critical need for target-ed interventions for depression in this population. Here we first describe translational animal model studies of the impact of housing at altitude on depression-like behavior (DLB) and antidepressant function. Further, we describe clinical trials of non-traditional adjunctive treatments to correct hypoxia-linked neurochemical deficits in Utah women with TRD: with creatine monohydrate (CrM) to correct bioenergetics (Kondo 2016; Kondo, 2011) or with combination therapy of 5HTP+CrM to improve both serotonergic and bioenergetic deficits.
I. Animal Studies:
Animals: Male and female Sprague Dawley (SD) rats were received from Charles River (Raleigh, NC). All procedures were approved by the Institutional Animal Care and Use Committees of the University of Utah and the Veterans Affairs Salt Lake City Health Care System, and were performed in accordance to the NIH Guide for Care and Use of Laboratory Animals.
Altitude Simulations: The altitude groups consist of sea level (SL), 4,500ft (4.5K) and 10,000ft (10K), plus a 20,000ft (20K) group in Study 1. Animals were housed in barometric chambers used to alter the ambient pressure at our facility (4,500ft): the hyperbaric chamber mimicked SL conditions (21% ppO2), and the hypobaric chamber mimicked 10K (15% ppO2) and 20K (10% ppO2), while the 4.5K group was housed at local conditions (18% ppO2) adjacent to the altitude chambers.
Forced Swim Test (FST): The FST is a well-established test for DLB and antidepressant function, widely used in pre-clinical antidepressant development (Bogdanova, 2013).
After a week at altitude, rats were tested for DLB in the modified FST (Kanekar 2015). In the FST, a rat is placed in a clear tank (25cm diameter, 65cm tall) filled to 48cm deep water at 25oC (Detke, 1996), and behavior videotaped. The FST is conducted in 2 sessions: a conditioning pretest and 24hrs later, the test FST to assay for DLB.
Treatment: In study 2, rats were injected with antidepressant or vehicle (C) at 1 hr, 19 hrs and 23 hrs after the pre-test FST (Detke 1996). Antidepressants were tested at optimal doses shown to be effective in the FST (Detke 1996): fluoxetine hydrochloride (Prozac®, 20mg/kg), paroxetine hydrochloride (Paxil®, 20mg/kg), escitalopram oxalate (Lexapro®, 20mg/kg), sertraline hydrochloride (Zoloft®, 10mg/kg), or the TCA desipramine hydrochloride (8mg/kg, positive control).
Data Analysis: FST behavior is presented as percent time spent swimming, climbing or immobile. Latency to immobility (LTI) is the time taken to achieve the first 10 sec of immobility (Kanekar 2015). DLB in the FST is a measure of behavioral despair in response to the inescapable stress of forced swim (Bogdanova 2013). Increased immobility and a shorter LTI represent DLB in the FST, and antidepressants reduce immobility and increase LTI by ≥20%. Serotonergic antidepressants (SSRIs) improve DLB by increasing swimming, while noradrenergic/do-paminergic antidepressants (desipramine) increase climbing (Detke 1996).
Data was analyzed by two-way analysis of variance (ANOVA) to investigate effects of altitude and gender (Study 1), or altitude and treatment (Study 2). Data is presented as mean ± standard error of the mean (M±SEM). Statistical significance was determined at p<0.05, presented after Bonferroni corrections.
II. Clinical Trials
All studies were approved by the University of Utah Institutional Review Board.
Study 1. Dietary Cr in Treatment-Resistant Adolescent Females:
Inclusion Criteria: Participants were women between 13-20yrs of age with a primary diagnosis of MDD, with fluoxetine (Prozac®, open-label study) (Kondo, 2011) or equivalent SSRI dose (placebo-controlled study) (Kondo 2016) treatment for ≥8wks with ≥4wks at a dose of ≥40 mg/day, and a Children’s Depression Rating Scale-Revised (CDRS-R) raw score ≥40 at screening. Exclusion criteria included renal dis-ease, psychotic symptoms or active problematic use of alcohol or illicit drugs. Complete blood count, metabolic panel, and urinalysis were obtained at baseline and at study conclusion.
Treatment and Outcome Analyses: In the open-label study, MDD patients received Creapure® brand CrM (AlzChem AG, Trostberg, Germany), 4g oral daily for 8wks (Kondo, 2011). In the placebo-controlled study, participants were randomly assigned to 2g, 4g or 10g CrM or placebo daily for 8wks (Kondo 2016). Vital signs and adverse signs were recorded at each visit. Rating scales administered were the CDRS-R, the Clinical Global Impressions scale-Severity (CGI-S) and the Columbia Suicide Severity Rating Scale (C-SSRS). The primary outcome was change in CDRS-R score from baseline. In vivo 31P-MRS neuroimaging was used to measure brain metabolites involved in cellular energy production, including Cr, phosphocreatine (PCr) and b-nucleotide phosphates (measuring adenosine triphosphate or ATP), vs. a baseline of total phosphate resonance (TP). 31P-MRS scans were conducted on participants prior to and after treatment, and on age-matched healthy control adolescents.
Study 2. Dietary 5HTP+Cr in Treatment-Resistant Adult Women:
Inclusion Criteria: Adult women were recruited with moderate-severe MDD at baseline as measured by Hamilton Depression Rating Scale (HAM-D) scores ≥16, with ≥8wks of treatment with an SSRI or serotonin norepinephrine reuptake inhibitor (SNRI) (Kious, 2017). Exclusion criteria included psychotic symptoms, seizure disorder and history of serotonin disorder.
Treatment and Outcome Analyses: Open-label treatment consisted of dietary 5HT-P+CrM for 8wks, with visits at 1wk, 2wks, 4wks, 6wks and 8wks, and 2 post-treatment visits (10wks, 12wks). Participants received 5g of Creapure® and 100mg Fuller Enterprise’s 5HTP (Fuller En-terprise Inc., Ontario, Canada) daily for 8wks, to supplement ongoing SSRI/SNRI treatment. Study outcomes were measured by HAM-D, Montgomery-Asberg Depression Rating Scale (MADRS), CGI-S, and Beck Anxiety Inventory (BAI) scales. C-SSRS and Young Mania Rating Scale (YMRS) identified adverse effects. Since 5HTP is linked to serotonin syndrome and/or eosinophilia myalgia syndrome (Turner, 2006), subjects were screened at each visit. Blood tests were conducted at screening and follow up. Primary outcome was a change from baseline HAM-D scores. HAM-D, MADRS and BAI scores were analyzed by repeated-measures linear mixed model, with Sidak correction for multiple comparisons. Statistical significance was defined as p<0.05.
I. Animal Studies
Study 1. Altitude and Depression:
Rats were tested for DLB in the FST after a week of housing at SL, 4.5K, 10K or 20K (Kanekar 2015). For LTI, two-way ANOVA showed no effect of gender, a strong effect of altitude (p<0.0001) and of their interaction (F(3,88)=12.8, p<0.0001, Fig 1A, 1C). In females, LTI decreased significantly with altitude (F(3,44)=28, p<0.0001), but not in males. For immobility, a significant effect was seen of altitude (p=0.014) and of the interaction be-tween altitude and gender (F(3,88)=9.5, p<0.0001). Immobility increased significantly with altitude in females, but not males (F(3,44)=10.5, p<0.0001, Fig 1B, 1C). For swimming, a significant effect was seen of altitude (p=0.0005) and of its interaction with gender (F(3,88)=7.2, p=0.0002). In females, swimming decreased significantly with altitude (F (3, 44) = 11.8, p<0.0001), but climbing did not change (Fig 1C). Males were similar in FST behavior across groups (Fig 1C).
Study 2. Altitude and SSRI Function:
After housing for a week at SL, 4.5K or 10K, female rats were treated with the SSRIs fluoxetine, paroxetine, escitalopram or sertraline, or the TCA desipramine and tested for DLB in the FST (Fig 2) (Kanekar, 2018). For LTI, two-way ANOVA showed a main effect of treatment (p<0.0001), none of altitude (p=0.3) and a significant effect of their interaction (F(10,266)=2.4, p=0.009, Fig 2A). For immobility, significant effects were seen of antidepressant (p<0.0001), altitude (p=0.01) and their interaction (F(10,267)=1.97, p=0.03, Fig 2B). For swimming, significant effects were seen of treatment (p<0.0001) and altitude (p=0.0006), and of their interaction (F(10,267)=2.6, p=0.004, Fig 2C). For climbing, a significant effect was seen of antidepressant (p<0.0001), but none of altitude or their interaction (F(10,268)=0.8, p=0.67, Fig 2D). In post hoc analysis, fluoxetine, paroxetine and escitalopram did not improve LTI or immobility. Fluoxetine and escitalopram did not improve swimming, as expected of SSRIs in the FST, but paroxetine and sertraline did. Surprisingly, fluoxetine, paroxetine and escitalopram significantly decreased climbing. Sertraline was the only SSRI to exhibit strong antidepressant efficacy across altitude groups, significantly increasing LTI and decreasing immobility by improving both swimming and climbing, as previously documented (Page, 1999). Desipramine served as a good anti-depressant by augmenting climbing as previously seen (Detke 1996).
(1) Housing for a week at moderate altitudes (4.5K, 10K) incrementally increases DLB in female rats. (2) The SSRIs fluoxetine, paroxetine and escitalopram lose efficacy in female rats at altitude, while sertraline is functional at altitude. Desipramine also works at altitude, but cardiac toxicity and lethality in overdose limits its clinical use (Preskorn, 1996).
II. Clinical Trials
Study 1. Dietary CrM in Treatment-Resistant Adolescent Females:
Five patients completed 8wks of adjunctive CrM and 31P-MRS scans in the open-label study, with no adverse effects seen in vital signs, laboratory tests or behavior (Kondo, 2011). Mean CDRS-R score decreased by an average of 56% from 69±9 (M±SD) to 31±8 after treatment (Fig. 3A). After 8wks treatment, depressed adolescents exhibit a significant increase in forebrain PCr/TP (p=0.02, paired t-test) vs. healthy controls. Participants’ CDRS-R scores inversely correlated with the change in PCr/TP (p<0.04). Four of 5 MDD patients endorsed a history of suicidality: 4 had suicidal ideation, and two attempted suicide prior to this study. During treatment, two reported no suicidal ideation, while suicidal ideation resolved during the study in others, and remained absent at the 10wk follow-up visit.
In the placebo-controlled dose-ranging study, participants were randomized to receive placebo or CrM at 2g, 4g or 10g daily for 8wks (n=6-8/treatment). A drop in CDRS-R scores was seen across treatment groups (Kondo 2016). Pre- and post-treatment 31P-MRS scans revealed higher frontal lobe PCr/TP levels after CrM treatment, but not in placebo controls (Fig 3B): PCr/TP increased by 4.6% at the 2g dose, 4.1% with 4g, and 9.1% with 10g, while the placebo group showed a 0.7% drop. Lower depression scores correlated to higher forebrain PCr/TP (p<0.02, Fig 3C).
Study 2. Dietary 5HTP+CrM in Treatment-Resistant Adult Women:
Twelve women (average age of 34±11yrs) completed the study (Kious, 2017), 10 were on SSRIs and two were on SNRI. 5HTP+CrM was safe and well tolerated, with no evidence of serotonin syndrome, eosinophilia myalgia syndrome or other adverse effects. No treatment-emergent mania or hypomania (by YMRS scale) was seen, or nor was treatment-emergent suicidal ideation identified based on C-SSRS.
At baseline, participants exhibit moderate-severe MDD with mean HAM-D score of 19±2, MADRS score of 25±4 and CGI-S score of 4±0.3. After 8wks treatment, HAM-D scores reduced by 60% to an average of 7.5±4 (Fig 4A), with response criteria (≥50% reduction) met by 10 patients and remission criteria (score ≤7) met by 7 patients. Mean MADRS scores decreased by 65% to 9±6 (Fig 4B), with 12 patients meeting response criteria and 8 patients meeting remission criteria (score<10). Anxiety levels improved, with a 60% drop in BAI scores from 22.7±9 to 9.3±6 (Fig 4C). Depression severity in the CGI-S improved from 4.1±0.4 to 1.9±1. Significant improvements were seen within a week of treatment (p<0.00001, Fig 4).
(1) CrM supplementation of SS-RI-treated treatment-resistant adolescent women improved depression status and suicidal ideation over 8wks, paralleled with improved forebrain bio-energetics. (2) 5HTP+CrM augmentation of SSRI/SNRI-treated treatment-resistant adult women improved MDD and anxiety status, with a good safety profile.
In our animal model, housing at altitude induced increased depression in female rats (Kanekar 2015). Female rats at altitude did not respond to the SSRIs fluoxetine, paroxetine and escitalopram (Kanekar, 2018), which are primarily serotonergic (Damsa et al., 2004). The SSRI sertraline functioned well at altitude, potentially due to its ability to enhance dopaminergic as well as serotonergic neurotransmission (Kanekar, 2018; Page 1999). In recent studies, rat brain serotonin levels decrease with housing at altitude, particularly in the striatum and prefrontal cortex, brain regions involved in mood regulation (C.S. Sheth, unpublished observations). We also find that anxiety and anhedonia (the inability to derive pleasure from pleasurable activity) increase in female rats at altitude (Sheth, 2018). These studies thus suggest that living at altitude or with chronic hypoxic diseases may decrease brain serotonin levels to worsen the status of depression and anxiety disorders, and may also render SSRIs ineffective.
Since SSRIs form over 80% of the US market for antidepressants and anxiolytics, this likely worsens rates of unresolved mood disorders at altitude, and may be responsible for the heightened rates of suicidal ideation seen in women in the Rocky Mountain States. Given the significantly lower basal brain serotonin in women vs. men, women living at altitude or with chronic hypoxic disorders may be particularly vulnerable to worsened mood and SSRI treatment-resistance. Women in the high-altitude Rocky Mountain States, Utah included, may thus suffer from unresolved mood disorders despite attempts to medicate with antidepressant use, thus suggesting the need for novel non-traditional therapeutics for altitude-related mood disorders.
We therefore conducted clinical trials of compounds directed at improving altitude-related deficits in bioenergetics (CrM) and serotonin (5HTP). Supplementing CrM in SSRI-resistant adolescent women improved depression status and brain bioenergetics (Kondo 2011, 2016). Improving brain bioenergetics is proposed as a mechanism for enhancing antidepressant response (Iosifescu 2008), and dietary CrM was initially shown to improve brain bioenergetics in healthy adults (Lyoo, 2003). Also, CrM augmentation of escitalopram-treated women improved SSRI response vs. escitalopram+placebo (Lyoo 2012). CrM treatment may thus enhance brain bioenergetics, to hasten antidepressant response and enhance clinical remission in depressed women. Our current study suggests that CrM improves response and remission criteria in TRD women. Additionally, CrM-linked enhancement in fore-brain PCr/TP correlates with improved depression scores, suggesting a mechanism of action (Kondo 2016). A placebo-controlled study of 10g CrM for treatment-resistant adolescent women is currently in process.
Our study of 5HTP+CrM augmentation in depressed treatment-resistant adult women is the first trial of combination therapy simultaneously targeting bioenergetics and serotonin synthesis (Kious, 2017). The intermediate metabolite in serotonin synthesis, 5HTP is readily converted to serotonin (Turner 2006). In clinical trials, dietary 5HTP showed antidepressant efficacy in an aver-age of 56% of MDD patients within 2-4wks (Turn-er 2006). Our clinical trial is a small scale open-la-bel study without placebo control, yet it suggests that 5HTP+CrM therapy may be a feasible new approach to TRD in women. A placebo-controlled study of 5HTP+CrM is currently in progress in SSRI/SNRI-resistant adult women.
These clinical studies show that novel antidepressant therapeutics targeted to improving hypoxia-related brain deficits in bioenergetics and serotonin may serve as more effective antidepressants for those living at altitude or with chronic hypoxic diseases.
While the consequences of extreme high altitude exposure (>18,000ft) have been studied for decades with regards to mountaineering, only recently has living at moderate altitudes (2000ft-10,000ft) been suggested to impact human mood and quality of life (Brenner, 2011; Maa, 2010). The human brain consists of about 2% of our body weight, but utilizes 20% of the body’s energy at rest. With the high basal oxygen needs of the brain, neurological symptoms including headaches, sleep disruption and mood disorders are prevalent in the chronic hypoxia experienced at altitude (Maa, 2010). As more people move to reside or vacation at moderate altitudes, addressing the physiological consequences of long-term altitude exposure becomes critical. The studies we describe here are an initial effort to understand the impact of living at moderate altitudes, such as in Utah, Colorado, and the other Rocky Mountain states, on brain physiology, mood status and anti-depressant function.
Hypoxia exposure can alter brain neurochemistry to promote biomarkers for depression and suicidal behavior (Gould, 2017). In animal models, hypoxia disrupts neurotransmitter balance, increases inflammation and cell stress, and lowers metabolic function in key brain regions involved in mood disorders (Gould, 2017; Kumar, 2011). In animal models, hypoxia is linked to low brain serotonin levels. Low brain serotonin in humans is implicated in greater depression, anxiety, impulsivity, risk-taking behavior and aggression, each of which is also linked to suicidal behavior. Further studies with our animal model may thus be of high relevance in studying hypoxia-related brain and behavioral deficits which may alter susceptibility to suicidal behavior, and, combined with clinical trials, will help us critically evaluate novel potential therapeutics for MDD in chronic hypoxia.
Chronic hypoxia exposure may worsen MDD and impair antidepressant function. With greater vulnerability to hypoxia, women living at altitude or with chronic hypoxic diseases likely suffer from a greater burden of MDD-linked health issues, poor quality of life and suicidal ideation, suggesting a critical need for effective antidepressant interventions in this population. Targeted therapeutics may be required for depressed women at altitude: the current studies identify sertraline, adjunctive CrM or 5HTP+CrM as promising antidepressant therapeutics for women exposed to chronic hypoxia. Given the high rates of depression and suicidal behavior documented in women living in the high-altitude Rocky Mountain States, the success of these studies are likely to be of considerable beneficial impact.
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Sexual Violence in Utah: The Relationship between Sexual Education and Sexual Violence
In 2017, Utah Representative Brian King proposed a comprehensive sexual education bill. H.B. 215. This bill included an emphasis on teaching sexual consent, and permitted parents to choose abstinence-based, comprehensive, or no sexual education for their children. While Utah lawmakers admitted there was a need for sexual education reform, they ultimately rejected the bill (Wood, 2017). This choice seems untimely, as rates of sexual assault in Utah consistently rank higher than the national average (Public Health Indicator Based Information System [IBIS], 2018; Utah Department of Health, 2014). Sexual violence is a comprehensive term that includes various sexually related crimes. “Sexual assault is any unwanted sexual contact or attention resulting from force, threats, bribes, manipulation, pressure, or violence” (Utah Department of Health, 2014). Sexual assault includes, but is not limited to, rape, attempted rape, unwanted sexual touch or fondling, and childhood sexual abuse (CSA).
Supporters of H.B.215 implicated Utah’s abstinence-based sex education for the state’s alarming rate of sexual violence, claiming it fails to teach students about healthy sexual relationships and how to identify sexual assault (Wood, 2017). Evidence suggests a possible relationship between abstinence-based sexual education and rates of sexual violence. More specifically, research indicates that abstinence-based sexual education curricula, like that taught in Utah, fosters sexual violence by teaching gender stereotypes, placing the onus of sexual assault on victims, and neglecting to educate young people about consent and recognizing sexual assault (Edwards, Bradshaw, & Hinsz, 2014; Fava & Bay-Cheng, 2013; Lamb, Graling, & Lustig, 2011; Lundgren & Amin, 2015; Schalet et al., 2014).
There are numerous examples of implicit and explicit gender stereotypes and gender biases in abstinence only curricula (Lamb et al., 2011). Schalet et al. even posits that many abstinence-based programs “…have taught gender stereotypes as facts” (2014). Curricula attribute specific, biologically-determined roles to males and females, presenting males as “unstoppable” hormonally driven sexual initiators, and females as passive sexual objects bereft of independent sexual desire (Lamb et al., 2011; Schalet et al., 2014). Researchers concur that gender stereotypes, gender inequalities, and the cultural attitudes that allow them to exist, are among the major risk factors for sexual violence (Fava & Bay-Cheng, 2013; Lamb et al., 2011; Lundgren & Amin, 2015; Schalet et al. 2014). Evidence links certain gender stereotypes, specifically relating to masculinity, with hostile attitudes towards women, intimate partner violence, and sexual aggression (Edwards et al., 2014; Lamb et al., 2011; Schalet et al., 2014). “Compared to other men,” reports Schalet et al. (2014), “ men who report more traditional masculinity ideologies are more likely to report having perpetrated violence or sexual coercion.” The female stereotypes portrayed in abstinence-based curricula are equally harmful; traditional feminine gender roles are associated with reduced sexual autonomy and sexual negotiating power, and higher risk for sexual violence (Lamb et al., 2011; Lundgren & Amin, 2015; Schalet et al., 2014).
These attitudes regarding gender norms, along with moralistic tactics common in abstinence programs, are particularly inimical towards sexual assault victims and sexually active teens (Fava & Bay-Cheng, 2013). Presenting sexual experience as a type of moral failing can influence attitudes that view these groups as irreparably damaged and incapable of having healthy sexual relationships in the future (Fava & Bay-Cheng, 2013). Fava & Bay-Cheng (2013) report that “…negative sexual self-schemas (i.e. belief that one is sexually damaged, immoral, and dirty) [are] related to adolescent revictimisation experiences of sexual assault in young women with a history of CSA.” Additionally, in Lamb et al.’s analysis of abstinence curricula, they found “…messages [that] imply that women are partly responsible for their own victimization” (2011). Sexual assault victims already experience higher levels of shame, and victim blaming could potentially be retraumatizing (Fava & Bay-Cheng, 2013). In turn, victim blaming reinforces gender stereotypes (men are unable to control their desires and women are the gatekeepers of sexual activity) and obscures the concept of consent (Lamb et al., 2011, Schalet et al., 2014). Gender norms may also stigmatize male sexual assault victims, rendering them more reticent to report or disclose assault (Schalet et al., 2014).
Abstinence-based sexual education programs habitually teach “refusal tactics” in lieu of sexual consent (Lamb et al., 2011). This distinction is important because research on sexual aggression reveals that many individuals experience difficulty in identifying various forms of sexual assault (Edwards, et al., 2014). Edwards et al. found that (Figure 1) Rape Rates in the Utah vs. the US when participants were presented with behavioral descriptions of sexual assault, men were more likely to admit to past sexually violent behavior than if the behavior was explicitly labeled (i.e. “rape”), and more women “self report[ed] past victimization” (2014). Clear education regarding different forms of sexual assault is critical for men who may not otherwise perceive their sexually aggressive behavior as rape, and for women who may not recognize their experiences as assault (Edwards et al., 2014).
National data suggest that as many as 1 in 5 women will be sexually assaulted in their lifetime (Edwards et al., 2014). In Utah, however, it is projected that 1 in 3 women will become victims of sexual assault (Utah Department of Health, 2014). In fact, Utah ranks 10th highest in number of reported rapes in the nation (Federal Bureau of Investigation, 2015). This is surprising as Utah’s rates of other violent crimes, such as homicide, aggravated assault, and robbery, historically have been significantly lower than the national average (IBIS, 2018). Rates of rape in Utah have been higher than the national average for over a decade (See Figure 1 and Table 1). In general, the national rate of rape is decreasing, but the rape rate in Utah is trending upwards (See Figure 1 and Table 1); between 2014 and 2017, Utah’s rape rate increased 10.7% (IBIS, 2018).
In 2013, 9% of female and 6% of male high schoolers reported being raped (Utah Department of Health, 2014; IBIS, 2018) but other research suggests the rate of adolescents’ exposure to sexual violence may actually be higher (Lundgren & Amin, 2015). It is estimated that 88% of Utah rapes remain unreported, making it difficult to accurately assess the severity of the issue (Utah Department of Health, 2014).
In terms of sex education, Utah is one of the 24 states in the country that mandates sexual education. Utah is also one of only 13 states that require curricula to be medically accurate. However, education regarding contraceptives is not required in Utah schools, and abstinence-only-until-marriage ideology is stressed (Guttmacher Institute, 2017).
7 Domains of Health
Sexual violence impacts the overall health and well being of girls and women in Utah. Approximately 13% of sexual assault victims seek medical treatment following the incident, leaving 87% of victims at risk of a sexually transmitted infection (STI) and/or pregnancy (IBIS, 2018; Utah Department of Health, 2014). Sexual violence can have long-term affects on physical health, chronic pain disorders, gastrointestinal disorders, premenstrual syndrome, chronic pelvic pain, sleep disturbances, sexual dysfunction, and generally poor health (IBIS, 2018).
Victims of sexual assault are at an increased risk for anxiety disorders, depression, substance abuse, and are “more likely to attempt or commit suicide” (IBIS, 2018). 15% of rape victims reported a diminished quality of life, and 34% expressed that they didn’t feel adequately emotionally or socially supported. Nearly 40% of rape victims disclosed they were “limited in activities because of physical, mental, or emotional problems” (IBIS, 2018). Women with histories of sexual violence are more likely to experience shame, guilt, and struggle with interpersonal relationships (Fava & Bay-Cheng, 2013). The Utah Department of Health reports that sexual violence cost Utahns approximately $5 billion dollars in 2011, and attributed the majority of the cost to “…the pain, suffering, and diminished quality of life that victims experience” (2014).
In 2001, Surgeon General David Satcher advocated for comprehensive sex education on the basis that youth “needed enough information about contraception to protect themselves from pregnancy and/or disease, that they needed to be protected from abuse, and they needed to be treated equally in a nondiscriminating way with regard to their sexual development” (Lamb et al., 2011). Other research certainly supports this appeal. Based on the data reviewed in this article, there are several key recommendations for sexual education reform in Utah that may ameliorate rates of sexual violence. First, sex education should be comprehensive and sex positive. Failing to educate youth about healthy sexual relationships, desire, and pleasure puts them, particularly girls, at risk for exposure to sexual violence (Lamb, et al., 2011; Schalet et al., 2014). Second, considering the relationship between gender stereotypes and sexual violence (Edwards, et al., 2014; Lamb et al., 2011; Lundgren & Amin, 2015; Schalet et al., 2014), sex education needs to be “free from harmful gender beliefs — which may be explicit or implicit in the curricula — and include tools to help students address and challenge these beliefs” (Schalet et al., 2014).
To more effectively combat stereotypes and damaging cultural attitudes, sexual education should also be LGBTQ+ inclusive, and considerate of racial and socioeconomic factors (Fava & Bay-Cheng, 2013; Schalet et al., 2014). Third, sexual education should be Trauma-Informed to prevent victim blaming and retraumatization of students with histories of sexual assault (Fava & Bay-Cheng, 2013; Lamb et al., 2011; Lundgren & Amin, 2015). Finally, sex education needs to be consent centered. Consent education promotes sexual autonomy (Lamb et al., 2011; Schalet et al., 2014) and disambiguates various forms of sexual assault (Edwards et al., 2014). Implementing these concepts into sex education curricula will aid in addressing the attitudes, beliefs, and inequalities that influence sexual violence. More direct research is necessary in the future to further investigate the relationship between sex education and sexual violence.
Edwards, S. R., Bradshaw, K. A., & Hinsz, V. B. (2014). Denying rape but endorsing forceful intercourse: Explor- ing differences among responders. Violence and Gender, 1(4), 188-193.
Fava, N. M., & Bay-Cheng, L. Y. (2013). Trauma-informed sexuality education: recognising the rights and resil- ience of youth. Sex Education, 13(4), 383-394.
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Guttmacher Institute. (2017) Sex and HIV Education. Retrieved from https://www.guttmacher.org/state-policy/ explore/sex-and-hiv-education. Accessed May 1, 2019
Lamb, S., Graling, K., & Lustig, K. (2011). Stereotypes in four current AOUM sexuality education curricula: Good girls, good boys, and the new gender equality. American Journal of Sexuality Education, 6(4), 360-380.
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Public Health Indicator Based Information System (IBIS). (2018). Complete Health Indicator Report of Sexual Violence. Retrieved from https://ibis.health.utah.gov/indicator/complete_profile/Rape.html. Accessed May 1, 2019
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Wood, B. (2017, February 7). Utah sex ed needs attention, legislators say, but abstinence angle will continue. The Salt Lake Tribune. Retrieved from http://www.sltrib.com/home/4910764-155/comprehensive-sex-ed-reject- ed-in-utah. Accessed May 1, 2019
Spencer J. (2019). Sexual Violence in Utah: The Relationship between Sexual Education and Sexual Violence. Utah Women’s Health Review. doi: 10.26054/0K7VFD5DKV.
In Utah, one in three women will experience some form of sexual violence (SV) during their lifetime, and one in eight women and one in 50 men will experience rape (Utah Department of Health, 2008). Utah ranks 10th in the nation for reported rape (U.S. Department of Justice, 2013). What makes this statistic particularly alarming is that “rape is the only violent crime in Utah that is higher than the national average” (U.S. Department of Justice, 2013). Other violent crimes, such as homicide, robbery or aggravated assault, are “historically half to three times lower than the national average”. The effects of SV can be physical, emotional, and/ or psychological. SV affects the immediate quality of life and can have lasting consequences for survivors. When compared to individuals who are not raped, rape survivors have been found to have a significantly higher prevalence of reporting dissatisfaction with life (14.7% vs. 4.8%); not receiving the social and emotional support they need (33.8% vs. 13.2%); reporting fair or poor health (25.9% vs. 10.7%); and experiencing activity limitations because of physical, mental, or emotional problems (39.2% vs. 19.7%; Utah Department of Health, 2010).
Public health approaches SV through primary prevention, defined as preventing SV before it occurs. Public health personnel are concerned with approaches that can affect people and the communities where they live, learn, work, and play; and these approaches may include involving entire communities to prevent SV, as SV affects everyone directly or indirectly. In order to conduct primary prevention through all levels of our society, various sectors must be engaged, including policy makers.
Prevention strategies focus on policy, social norms, and increasing protective factors, as well as decreasing risk factors for SV. With this goal in mind, the Utah Department of Health Violence and Injury Prevention Program, in partnership with the Utah Coalition Against Sexual Assault, put together a whitepaper called the Costs of Sexual Violence in Utah (Cowan, 2015). This report was designed to guide SV prevention resources throughout the state.
n 2015, the Utah Department of Health, together with the Utah Coalition Against Sexual Assault, compiled data highlighting the economic burden of SV. The figures and data in this snapshot are from that report. The report looks at child (0-17 years) sexual assault and adult (18+ years) incidents of rape and sexual assault. To estimate the cost of SV in Utah, existing data were used and methodology was adopted (Cowan, 2015). Cost categories factored in economic health, emotional health, physical health, and occupational/ financial health of the individuals. Furthermore, the report looked at Utah government spending for prevention, as well as government spending on survivors and on perpetrators (oversight and confinement).
In 2011, in Utah an estimated 3,609 children ages 0-17 were victims of sexual assault. That same year, there were 20,666 adult rape victims and 54,742 adult other sexual assault victims (Table 1). The majority of sexual assault and rape victims were female, including 63% of child sexual assault victims, 84% of adult rape victims, and 75% of adult other victims of other forms of sexual assault.
When all cost categories for the entire Utah population were aggregated, the 2011 direct and indirect costs of SV was $4.9 billion. That breaks down to over $800 million for child sexual assault and over $4 billion for adult rapes. The cost per SV incident in 2011 was an average of $184,504 for children per incident. For adults, rape costs were $154,598 per incident and other sexual assault costs were $282 per incident. For adult rapes, the largest cost category, suffering and lost quality of life, came out to $126,713 per adult rape incident. Additionally, mental health care cost $3,610 per adult rape incident, suicidal acts cost $7,535 per incident, and substance abuse costs per adult rape are $5,039 per incident. These costs are significant to both the individual and society.
In 2011, government spending in Utah related to SV totaled more than $109 million (Table 2). Estimated spending on sexually violent offenders was higher than spending on victims who were raped or sexually assaulted for the one year. Utah spent over $92 million (84.4%) on offenders, including costs of investigation, confinement, and the sex offender registry. It is important to note that the Rape, Abuse, & Incest National Network (www. rainn.org) estimates that the majority of rapes are not reported to the police and only about 0.6% of rapists will be incarcerated, suggesting that the vast majority of perpetrators are not included in the offender cost category. That same year, Utah spent just under $16.5 million (15.1%) on victims of SV, primarily on medical bills for victims on Medicaid, sexual assault examination payments, and child protective services. Finally, $569,000, or just 0.5% of government funding, was spent on prevention programs (Cowan, 2015).
As documented, there are substantial health and economic consequences of SV. Furthermore, connections can be made to SV across all domains of health. This impact can and should have policy implications, and may be addressed through policy change.
Physical & Reproductive Health – The very act of SV violates a person’s agency over her or his own body and denies her or him the right to decide when and how to engage sexually, as well as potential for unwanted pregnancy, potential for sexually transmitted infections (STIs), injury to repro- ductive organs, and overall physical injury. The Adverse Childhood Experiences study associates SV victimization in childhood to higher rates of chronic disease and adverse health behaviors later in life (Krug, Dahlberg, Mercy, Zwi, & Lozano, 2002; Sommers, 2007).
Social Health – SV is shown to have impacts on victims’ social health, including: strained relationships with family, friends, and intimate partners; diminished emotional support from and contact with friends and family; decreased likelihood of marriage; and isolation or ostracism from family or community (Jacqueline M. Golding, 2002; Krug et al., 2002).
Emotional Health – Emotional health consequences of SV result from other impacts on the domains of health, as seen in the Social Health section. For example, victims of SV can experience both immediate and chronic emotional/psychological health consequences, including but not limited to: anxiety; withdrawal; distrust of others; post-traumatic stress injury; depression; attempted or completed suicide; and low self-esteem/self-blame (Campbell & Dworkin, 2009; Goodman, Koss, & Russo, 1993; Yuan, Koss, & Stone, 2006).
Occupational and Financial Health – As a result of SV, victims often suffer occupational and financial
burdens, including time off from work without pay or loss of work, as well as overall lost productivity. The financial burden of SV victimization includes medical and mental health care costs, in addition to other related costs such as property damage, pregnancy (not to mention child rearing), and potentially housing or relocation issues.
Intellectual Health – Given that the majority of victims of SV experience first-time victimization before the age of 25, we know that the educational achievement, and therefore the intellectual health, of victims is at risk. This is due, in part, to the diminished opportunity to learn in a safe and equitable environment, and individuals who have experienced SV may miss school as a result of their victimization. The intellectual health and academic achievement of victims is gaining increased attention as educational institutions work to comply with the Title IX law.
Several implications that affect policy have been identified from the Costs of Sexual Violence Report (Cowan 2015).
SV results in a large expense to society.
There is a lack of priority placed on prevention in Utah. Funding prevention efforts has the potential to result in reduced costs for perpetrator and victim services incurred by the government, in addition to reducing the financial burden on society that inevitably picks up some of the remaining non-governmental spending costs and additional intangible costs.
It should be noted during the 2016 and 2017 legislative sessions in Utah the Department of Health received appropriations from the federal Temporary Assistance for Needy Families Fund (https://www.benefits.gov/benefit/613) to allocate to local programs in order to implement SV primary prevention activities. Since these are one-year, one-time funds, a more sustainable approach to
funding to address SV prevention in Utah is necessary.
By bringing to light the economic impact of SV on Utah communities, we hope to educate about strat- egies that would help reduce costs effectively, as well as help with the evaluation of SV prevention approaches to address these problems in the best way possible. For more information on SV, including SV prevention in Utah, please visit http://health.utah. gov/vipp/topics/rape-sexual-assault/.
Campbell, R., Cabral, G. & Dworkin, E. (2009). An Ecological Model of the Impact of Sexual Assault on Women’s Men tal Health, Trauma Violence Abuse 10(3), 225–246. https://doi.org/10.1177/1524838009334456
Cowan, L. (2015). Costs of Sexual Violence in Utah 2015. Salt Lake City, Ut. Retrieved from https://justice.utah.gov/ Violence/Documents/costs-sexual-violence-report.pdf
Goodman, L. A., Koss, M. P., & Russo, N. F. (1993). Violence Against Women: Physical and Mental Health Effects.
Applied and Preventive Psychology, 2(2), 79–89. Retrieved from https://arizona.pure.elsevier.com/en/ publications/violence-against-women-physical-and-mental-health-effects-part-i-
Jacqueline M. Golding, S. C. W. and M. L. C. (2002). Sexual Assault History and Social Support: Six General Population Studies. Journal of Traumatic Stress, 15(3), 171–266. https://doi.org/10.1023/A:1015247110020
Krug, E. G., Dahlberg, L. L., Mercy, J. A., Zwi, A. B., & Lozano, R. (2002). World report on violence and health. Retrieved from http://apps.who.int/iris/bitstream/10665/42495/1/9241545615_eng.pdf
Sommers, M. S. (2007). Defining Patterns of Genital Injury from Sexual Assault, 8(3), 270–280. https://doi. org/10.1177/1524838007303194
U.S. Department of Justice. (2013). Crime in the United States by State, 2013. Retrieved from https://ucr.fbi.gov/crime- in-the-u.s/2013/crime-in-the-u.s.-2013/tables/5tabledatadecpdf/table_5_crime_in_the_united_states_by_ state_2013.xls
Utah Department of Health. (2008). Sexual Violence. Utah Health Status Update. Retrieved from https://ibis.health. utah.gov/pdf/opha/publication/hsu/2008/08Apr_SexualViolence.pdf
Utah Department of Health. (2010). Behavioral Risk Factor Surveillance System. Retrieved from http://ibis.health.utah. gov/query/selection/brfss/BRFSSSelection.html
Yuan, N. P., Koss, M. P., & Stone, M. (2006). The Psychological Consequences of Sexual Trauma. VAWnet.org National Online Resources Center on Violence Against Women, (March). Retrieved from http://vawnet.org/sites/de fault/files/materials/files/2016-09/AR_PsychConsequences.pdf
Waters M & Ferrell D. (2019). Cost of Sexual Violence in Utah. Utah Women’s Health Review. doi: 10.26054/0KBN5JFNFS.
Postpartum depressive symptoms (PDS) can range from the “baby blues”—when for a short period of time after childbirth, a mother experiences mood swings, anxiety, sadness, and/or appetite/sleeping problems—to postpartum depression (PPD)—which involves similar signs and symptoms but is experienced more intensely and for a longer period of time, and may interfere with a mother’s ability to care for her baby and herself. Up to 80% of women in the United States may experience transient PDS, and up to 12% are estimated to experience PPD (Ko et al., 2017). If left untreated, moderate to severe PPD has been linked with lower rates of breastfeeding duration and initiation, impairment of mother-infant bonding, and delayed social and cognitive development of offspring (Ko et al., 2017).
Timing is the only aspect that distinguishes PDS or PPD from other types of depression. The American Psychiatric Association defines PPD as a major depressive episode with onset in pregnancy or within 4 weeks after delivery (American Psychiatric Association, 2015). A new mother who experiences three or more out of the following symptoms in the same period, in addition to depressed mood and loss of interest or pleasure, would be diagnosed with PPD:
Change in weight or appetite. Weight: 5 percent change over 1 month;
Insomnia or hypersomnia;
Psychomotor retardation or agitation (observed);
Loss of energy or fatigue;
Feelings of worthlessness or guilt;
Impaired concentration or indecisiveness;
Recurrent thoughts of death or suicidal ideation or attempt.
Given the serious consequences of postpartum depression and its relatively high prevalence, a developmental Healthy People 2020 goal is to reduce the proportion of women who experience PDS after delivering a live birth. Healthy People 2020 defines this as a developmental objective since the condition lacks national baseline data. Consequently, no technical specifications for improvement are specified; however, a nationally representative data source that can provide a tracking point exists. Furthermore, it is acknowledged that this is an important concern deserving of monitoring for improvement (Office of Disease Prevention and Health Promotion).
Given evidence supporting that PDS and PPD are treatable via pharmacologic therapy and/or behavioral interventions (Ko et al., 2012), the key to reducing morbidity and mortality associated with this maternal condition is proper screening, diagnosis, and treatment of at-risk mothers. Research conducted within the last decade indicates that nearly 60% of new mothers with depressive symptoms do not receive a clinical diagnosis and 50% of women with a clinical diagnosis do not receive any treatment (Ko et al., 2012). Consequently, several professional women’s health groups, including the American College of Obstetricians and Gynecologists, recommend that providers screen for depression at least once during pregnancy or postpartum. Some even advocate the need to screen pre-conceptionally, given that women with a history of depression have a two-fold increased risk of suffering from PPD (Gauthreaux et al., 2017).
Our objective in this data snapshot is to provide recent Utah statistics on prevalence of preconception and prenatal/postpartum depression screening and diagnosis, using the Pregnancy Risk Assessment Measurement’s Survey (PRAMS) for Utah. Additionally, we aim to compare current Utah statistics with those of the past and for the rest of the United States.
Utah Pregnancy Risk Assessment Monitoring System (UT-PRAMS) Methodology: Participants contributing responses for this data snapshot were mothers who participated in the Utah Pregnancy Risk Assessment Monitoring System (UT-PRAMS) between 2012 and 2014. Two questions were specifically related to PDS: 1) “Since your new baby was born, how often have you felt down, depressed, or hopeless?”; and 2) “Since your new baby was born, how often have you had little interest or little pleasure in doing things?” For both questions, women were given options of “Always”, “Often”, “Sometimes”, “Rarely”, or “Never”. As per the Centers for Disease Control (CDC) PRAMS methodology, we classified any woman who answered “Always” or “Often” as having PDS. Sociodemographic, lifestyle, and health history questions also make up the PRAMS questionnaire, in addition to inquiries about past history of depression and whether any health care provider discussed with them what they should do if they felt any depressive symptoms during or after their baby was born.
Women who answered either question in regards to PDS were included in the analysis (n=4328/4378, 99%). Descriptive characteristics including socio-demographic, psychosocial, and health factors of Utah mothers by PDS status (yes/no) were calculated by chi square or t-tests as appropriate, taking into account the stratified random sampling in the analyses. Key risk factors for Utah mothers were evaluated via adjusted Poisson regression to generate prevalence ratios (PR) and 95% confidence intervals. Analyses were completed using SAS version 9.4 (SAS Institute, Inc.). Utah Pregnancy Risk Assessment Monitoring System (UT-PRAMS) Results:
Prevalence of PDS among Utah women, 2012–2014, was 12.0%. In regards to demographic and health characteristics, women who experienced PDS compared to those who did not were more likely to be younger (27.3 vs 28.2 years), lower income (34.9% vs 19.2% ≤ 100% of Federal Poverty Level [FPL]), higher body mass index (BMI) (26.1 vs 25.3), to report a prior-to-pregnancy diagnosis of hypertension (3.8% vs 1.9%) and depression (29.0% vs 7.3%), and to report a 3-months-prior-to-pregnancy history of asthma (10.3% vs 6.9%), anemia (12.4% vs 7.1%), and/or anxiety (32.7% vs 11.4%) (Table 1). In regards to psychosocial and lifestyle factors, women with versus without PDS were more likely to report partner abuse prior to and during pregnancy (3.9% vs 1.3% and 4.0% vs 1.1%, respectively), 3-months-prior-to-pregnancy smoking (15.8% vs 8.4%) or alcohol (29.4% vs 23.2%) exposure, and presence of higher partner (43.7% vs 18.5%), traumatic (22.5% vs 10.1%), financial (57.4% vs 47.4%), or emotional (35.9% vs 27.6%) life stressors. Finally, women with versus without PDS were more likely to have a current (11.3% vs 7.4%) or prior (14.7% vs 9.6%) preterm birth (PTB) and more likely to have an unintended pregnancy (34.0% vs 21.6%).
In the adjusted analyses, after taking into account mother’s age, race, ethnicity, and BMI, the statistically significant predictors of PDS included being ≤100% of federal poverty level (PR: 1.48 [95% CI: 1.21, 1.82]), having had a prior diagnosis of depression or anxiety (PR 2.09 [95% CI: 1.58, 2.77]; PR 1.60 [95% CI: 1.22, 2.1], respectively), experiencing partner-related or traumatic-related stress (PR 1.76 [95% CI: 1.41, 2.20]; PR 1.24 [95% CI: 0.98, 1.55], respectively), and having a preterm birth infant for the most recent pregnancy (i.e., 2–4 months prior) (PR:1.35 [95% CI: 1.08, 1.69]) (Figure 1). None of the other factors listed in Table 1, including mother’s age, race, ethnicity, and BMI, significantly predicted a woman’s risk of PDS.
Current State of PDS in Utah compared to the Past and to the Rest of the United States In line with the majority of the US, which has witnessed a statistically significant decline in PDS from 2004 to 2012 among 13 states (with data for all periods), PDS in Utah has dropped from 14.8% in 2004 to 12.4% in 2008 to 11.3% in 2012 (P for trend = 0.01) (Ko et al., 2017). Among the 27 states participating in the 2012 PRAMS survey, Utah’s 11.3% PDS prevalence ranks 14th in the US (average: 11.5%; range 8.0 to 20.1). However, the 2013 to 2014 UT-PRAMS data do not support a continuing decline, with the prevalence going up to 12.5% in 2013 and 12.3% in 2014.
In terms of characteristics significantly associated with PDS, Utah was similar to the rest of the US, with PDS being higher in younger, unmarried, less educated, more highly stressed women who gave birth to a preterm infant. (Ko et al., 2017) What our results show for the UT-PRAMS 2012–2014 data is that the risk factors that are most predictive of PDS in Utah, after taking into account maternal age and race/ethnicity include 1) living below 100% of the federal poverty level; 2) a prior depression or anxiety diagnosis; 3) experiencing partner- or traumatic-related stress; and 4) having a preterm infant.
Our findings from the UT-PRAMS 2012–2014 survey highlight that approaching PDS truly requires a multidisciplinary approach, particularly in the domains of social, emotional, and financial support. The CDC points to several factors that may be linked to the reduced prevalence of PDS in the US from 2004 to 2012, including reduction in teen births, preterm births, and self-reported stressful life events as well as an increase in antidepressant prescriptions for pregnant women (Ko et al., 2017). Our findings from UT-PRAMS 2012–2014 indicate that new mothers who have a prior history of depression and anxiety are at significant increased risk for PDS and thus should be a subgroup who receive extra attention by healthcare providers in terms of appropriate screening, referral, and treatment (Practice, 2015) (Earls et al., 2010). Utah women who have experienced partner or traumatic-related stressors or who are in the lowest income brackets are also at high risk for PDS and deserve special consideration.
Finally, it is important to note that ~30% of women reported that their prenatal doctor, nurse, or other health care worker never talked with them during one of their prenatal care visits about what to do if they felt depressed or suffered from physical abuse during or after their pregnancy. While we found no difference in PDS risk by having or not having these discussions, professional women’s health organizations have come up with new strategies that may make these discussions more effective. Strategies include using validated screening tools (American College of Obstetricians and Gynecolo-gists, 2015) and extending maternal mental health screening to postpartum period during well-baby and/or primary care visits (Earls et al., 2010; Ko et al., 2017; Practice, 2015). Another useful resource for both health professionals and mothers/families is the Utah Maternal Health Collaborative, a state chapter of Postpartum Support International. Founded in September 2014, this is an all-volunteer organization made up of several hundred community members including survivors of maternal depression as well as healthcare providers (http://www.utahmmhc.org).
American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders, (5th ed.) (DSM-5). Washington, DC: American Psychiatric Publishing.
Earls, M. F., (2010). Incorporating recognition and management of perinatal and postpartum depression into pediatric practice. Pediatrics, 126(5), 1032-1039.
Gauthreaux, C., Negron, J, Castellanos, D., Ward-Peterson, M., Castro, G., Rodriguez de la Vega, P. & Acuña, J. M. (2017). The association between pregnancy intendedness and experiencing symptoms of postpartum depression among new mothers in the United States, 2009 to 2011: A secondary analysis of PRAMS data. Medicine, 96(6), e5851.
Healthy People 2020. Washington, DC. Department of Health and Human Services. Office of Disease Prevention and Health Promotion. Maternal, Infant and Child Health: Postpartum Health and Behavior. Available from https://www.healthypeople.gov/2020/topics-objectives/topic/maternal-infant-and-child-health/objectives. Accessed May 1, 2019
Ko, J. Y., Farr, S. L., Dietz, P. M., & Robbins, C. L. (2012). Depression and treatment among U.S. pregnant and nonpregnant women of reproductive age, 2005-2009. J Womens Health (Larchmt), 21(8), 830-836.
Ko, J. Y., Rockhill, K. M., Tong, V. T., Morrow, B. & Farr, S. L. (2017). Trends in Postpartum Depressive Symptoms – 27 States, 2004, 2008, and 2012. MMWR. Morbidity and Mortality Weekly Report, 66(6), 153-158.
Elmer A, McEwan M, Schliep K. (2019). Data Snapshot: Postpartum Depression. Utah Women’s Health Review. doi: 10.26054/0KYY9AQVJ2.
Breastfeeding and Mothers Own Milk is Best for Babies
Most mothers know that breastfeeding and providing expressed mothers milk is best for babies and is the normal standard for infant feeding and nutrition. According to the American Academy of Pediatrics (AAP) Breastfeeding and the Use of Human Milk Policy Statement, the committee states that “breastfeeding should be considered a public health issue and not only a lifestyle choice” (AAP 2012). The reason for this statement is the documented short- and long-term health and cognitive positive outcomes of breastfeeding. The AAP recommends exclusive breastfeeding for about 6 months and then continued breastfeeding once complementary foods are introduced for 1 year or longer (2012).
The Healthy People 2020 Breastfeeding Objectives mirror this recommendation and believe that breastfeeding and/or providing expressed mothers milk is a key public health strategy. One reason for this increase is the awareness of the impact of hospital practices and routines that support initiation and duration of breastfeeding. The Ten Steps to Successful Breastfeeding developed by WHO and UNICEF when implemented by hospitals has been shown improve breastfeeding rates. Breastfeeding rates are increasing nationally but still fail to reach any of the Healthy People 2020 Breastfeeding objectives.
Mothers’ milk provides more than the perfect nutrition at the right times in a newborn and infants life. It also provides non-nutritional benefits beginning with colostrum and continues for as long as the infant/child received mothers’ milk including after cessation of breastfeeding into adulthood. There are over 200 compounds found in mothers’ milk all working together to provide the necessary nutrition and immunologic protection while the infant’s immune system is maturing. Mothers milk has many roles; it transports nutrients, affects biochemical systems, enhances immunity and destroys pathogens. This is why benefits are seen with any breastfeeding and the longer the breastfeeding duration the more significant health risks are reduced producing (see table 1).
The health benefits and outcomes listed in table 1 are just the beginning. Breastfeeding and receiving mothers’ milk has been associated with a positive risk reduction of non-communicable diseases (NCD) into adulthood. Kelishadi and Farajian (2014) reported the reduction and prevention of the NCD’s as a public health issue as 63% of all-cause mortality are related to NCD’s. Kelishadi and Farajian (2014) report evidence is growing to support the role of breastfeeding in infancy to reduce risk and prevalence of hypertension, obesity, type 2 diabetes mellitus, hypercholesterolemia, and cardiovascular disease. Duration of breastfeeding is also associated with more protection later in life. The authors conclude the need for more longitudinal studies in these areas as some studies are conflicting with confounding factors and do not show a clear association. Despite this need for more research on NCD’s, the authors stress clear short- and long-term health benefits and reduction in risk with breastfeeding.
The health benefits associated with breastfeeding are significant. Recommendations are to exclusively breastfeed for 6 months and continue as mutually desired for at least one year. There are a few medical reasons a mother is not able to breastfeed her baby including a metabolic disorder and a few specific maternal infections. All mothers are encouraged to speak up and discuss concerns they have with an International Board Certified Lactation Consultant (IBCLC).
Recent studies have published the impact of suboptimal breastfeeding. Bartick et al. (2017) studied the costs associated with suboptimal breastfeeding. They report excess deaths in infants associated with suboptimal breastfeeding mostly due to Sudden Infant Death Syndrome (SIDS) with 492 deaths annually and with 92 deaths annually from necrotizing enterocolitis in the United States. Bartick et al. also reported 0.8 women need to breastfeed to prevent infant gastrointestinal infection, 3 women to breastfeed to prevent acute otitis media, and 95 to prevent hospitalization for lower respiratory infection. The authors conclude that “for every 597 women who breastfeed, one maternal or child death is prevented” (Bartick et al. 2017). Bartick and Reinhold in 2010 reported a cost savings of 13 billion dollars in the United States and 911 deaths prevented if 90% of mothers could breastfeed exclusively for 6 months. They also reported a cost savings of 10.5 billion and 741 lives saved if there was 80% compliance with the AAP and Healthy People breastfeeding recommendations.
Utah is one of only 10 states meeting all five Healthy People 2020 objectives in the 2016 CDC Breastfeeding report card (see Table 2). According to the CDC Breastfeeding Report Card, Utah has the highest initiation of breastfeeding in the country and the highest breastfeeding rates of breastfeeding at 6 months. Costs of suboptimal breastfeeding are much lower in Utah because of increased compliance with the AAP and Healthy People Guidelines.
Despite the high initiation and duration rates in Utah, work still needs to be done to improve exclusive breastfeeding rates at 3 and 6 months. According to the 2016 CDC Breastfeeding report card, 73% of infants in the state of Utah are not being exclusively breastfed at 6 months despite initiation of 94.4%. Providing education to mothers and families on these benefits has a significant impact on initiation and duration. Wallenborn, Perera and Masho (2017) report mothers who had knowledge of breastfeeding benefits were 5.6 times more likely to have longer duration of breastfeeding compared to women who did not have a greater knowledge of these benefits. Ongoing efforts are needed to continue to provide education and ongoing support for breastfeeding mothers.
American Academy of Pediatrics (2012). Committee on Nutrition, Section on Breastfeeding Policy Statement. Breastfeeding and the Use of Human Milk. Pediatrics, 129(5), e827-841, doi:10.1542/peds.2011-3552.
Bartick, M. and Reinhold, A. (2010). The Burden of Suboptimal Breastfeeding in the United States: A Pediatric Cost Analysis. Pediatrics, 125:e1048-e1056.
Bartick, M. C. et al. (2017). Suboptimal breastfeeding in the United States: Maternal and pediatric health outcomes and costs. Matern Child Nutr, 13(1). doi:10.1111/mcn.12366.
Centers for Disease Control (2016) Breastfeeding Report Card. Retrieved from https://www.cdc.gov/breastfeeding/pdf/2016breastfeedingreportcard.pdf accessed 6/29/2017.
Healthy People 2020. About Healthy People (2014). Retrieved from https://www.healthypeople.gov/2020/About-Healthy-People accessed 6/20/2017.
Kelishadi, R. and Farajian, S. (2014). The protective effects of breastfeeding on chronic non-communicable diseases in adulthood: A review of evidence. Adv Biomed Res, 2014 3(3). Doi:10.4103/2277-9175.124629.
Wallenborn, J. T., Perera, R. A., and Masho, S. W. (2017). Breastfeeding after Gestational Diabetes: Does Perceived Benefits Mediate the Relationship? J of Pregnancy, Article ID 9581796, 6 pages. Doi: 10.1155/2017/9581796
Lechtenberg E. (2019). Breastfeeding and Mothers Own Milk is Best for Babies. Utah Women’s Health Review. doi: 10.26054/0KD9B5MYQG.
The HealthyPeople initiatives use science-based objectives with the aim to improve health of Americans and disease prevention through awareness and improved understanding. The CDC Breastfeeding Report Card tracks progress of the HealthyPeople 2020 breastfeeding objectives nationally and by each state (Table 1). Breastfeeding and providing the mother’s own milk is well known to protect and improve health for infants with any breastfeeding; short and long-term breastfeeding and exclusive breastfeeding duration have long-term health outcomes that last through childhood into adult life. These health benefits are dose related and correlate with the HealthyPeople breastfeeding objectives. Breastfeeding and/or providing the mother’s own breastmilk protects mothers short-term and long-term, with improved health outcomes related to duration of breastfeeding or pumping. Dermer et al. reports that these breastfeeding benefits to mothers are a well-kept secret that is often unknown or not emphasized in education. Nationally, breastfeeding initiation rates are rising, with 29 states meeting the initiation objective. Duration rates are also increasing nationally; however, only 12 states met the 6-month objective for breastfeeding at 6 months. Utah has the highest initiation of breastfeeding in the country and the highest rates of breastfeeding at 6 months. Utah is one of only 10 states meeting all five HealthyPeople 2020 objectives in the 2016 CDC Breastfeeding report card (see Table 1).
Benefits that mothers obtain when they breastfeed are often understated and underemphasized. Maternal health is negatively impacted when mothers do not breastfeed or wean prematurely. Documented health outcomes studied in the literature include reduction of risk for breast cancer, ovarian cancer, type 2 diabetes mellitus, metabolic syndrome, obesity, hypertension, cardiovascular disease and postpartum depression. Many of these diseases are chronic non-communicable diseases (NCD) in adulthood and are attributed as major causes of mortality (Kelishadi and Faraijan, 2014). According to the World Health Organization (WHO) June 2017 Fact Sheet, NCD’s are responsible for 70% of all deaths globally, amounting to 40 million people. Cardiovascular disease is responsible for the most deaths from NCD’s followed by cancers, respiratory diseases, and diabetes (WHO 2017). Risk factors include being overweight/obese, hypertension, hyperglycemia and hyperlipidemia. All of these factors are associated with long-term risk reduction in mothers who breastfeed. The longer a mother breastfeeds, the larger the reduction risk of developing many of these NCD’s (Peters et al. 2017).
Schwarz and Nothnagle (2015) reported that breast and ovarian cancers are more common among mothers who did not breastfeed. According to their 2015 article, written following a meta-analysis of 47 studies, invasive breast cancer risk is reduced by at least 4%. The authors also reported that mothers with the BRCA1 mutation have a 37% reduction in breast cancer risk if they breastfeed for at least one year. Ovarian cancer is 32% more likely in mothers who did not breastfeed (Schwarz and Nothnagle, 2015). In 2016, Victoria et al. reported a reduction in invasive breast cancers by 4.3% for each 12-month increase in lifetime breastfeeding.
The American Academy of Pediatrics (AAP) reported similar percentages of breast cancer reduction for each year of breastfeeding. They also reported cumulative breastfeeding duration of greater than 12 months being associated with a 28% decrease in breast and ovarian cancer. Following a meta-analysis review, Victoria et al. reported that longer periods of breastfeeding were associated with a 30% reduction in ovarian cancer. These authors estimated that 20,000 maternal deaths are prevented annually at the current rate of breastfeeding, and another 20,000 breast cancer deaths could be prevented annually by improving breastfeeding practices. There is a growing body of evidence supporting improved metabolic health later in life in women who breastfeed. Schwarz and Nothnagle (2015) reported a significant reduction of risk of developing diabetes later in life for mothers who breastfed for at least one month. The authors also report a reduced risk of maternal obesity later in life. Mothers without a history of gestational diabetes showed a 4-12% reduced risk of developing type 2 diabetes mellitus, for each year of breastfeeding (AAP 2012).
According to data from the Women’s Health Initiative, cardiovascular disease risk was reduced by 28% after the first delivery in mothers who breastfed for seven to twelve months, compared to mothers who did not breastfeed. The Nurses’ Health Study looked at combined time of breastfeeding and documented that women who breastfed for a total of two or more years decreased their coronary heart disease risk by 23%, compared to mothers who did not breastfeed (Schwarz and Nothnagle 2015). Aortic calcification was significantly reduced in mothers who breastfed all of their children for at least 3 months. Mothers who did not breastfeed were five times more likely to develop aortic calcification compared to these mothers. The AAP Breastfeeding Policy Statement reports on the Women’s Health Initiative Study results, which included a signification reduction in hypertension, hyperlipidemia, and cardiovascular disease associated with cumulative breastfeeding of 12-23 months.
Maternal depression is clearly associated with a reduced prevalence in breastfeeding women. Women who do not breastfeed or who wean early have been observed to have higher rated of postpartum depression compared to breastfeeding mothers (AAP 2012). However, studies are not clear on whether breastfeeding reduces maternal depression or maternal depression impacts breastfeeding initiation and duration (Victoria et al. 2016).
Breastfeeding significantly decreases mortality from NCDs and all causes. Schwarz and Nothnagale reported that if 90% of mothers breastfed for one year, an estimated 14,000 heart attacks would be prevented and hypertension treatment would be avoided for 54,000 women. This could save the United States billions of dollars annually and prevent premature deaths in 4,000 women (Schwarz and Nothnagle 2015). Heart disease is the number one killer in Utah according to the American Heart Association (2015). Bartick et al. also reported on a cost analysis of maternal disease associated with suboptimal breastfeeding rates in 2012, and they determined annual maternal deaths in the United States as follows; 986 due to myocardial infarction, 838 due to breast cancer and 473 due to diabetes. The authors also indicated maternal medical costs of 2.37 billion dollars associated with suboptimal breastfeeding duration and 11.2 billion dollars associated with premature deaths. One last statistic from Bartick et al. estimates was that for every 597 women who optimally breastfed for one year, one maternal or child death was prevented. Review of Utah’s Public Health Data Resource consistently shows statistics of NCD prevalence in the state, where Utah is below the national average.
Using CDC Breastfeeding Report Card data, in 2917 Wallenborn, Perera and Masho reported that 51.8% of mothers across the United States breastfed to 6 months. In Utah that number was 70.4%. The authors reported that mothers who had knowledge of breastfeeding benefits were 11.2 times more likely to initiate breastfeeding and 5.6 times more likely to have longer duration of breastfeeding compared to women who did not have knowledge of these benefits. The authors concluded that breastfeeding as a behavior to reduce risk and possibly prevent illness is a dependent factor. Education to mothers on benefits to their baby is important; however, mothers also need to be provided education on short and long-term benefits for themselves as a method to improve breastfeeding duration. This can be done prenatally and in hospitals and physician offices following delivery. Practices that support breastfeeding are essential for mothers and babies. As Bartick et al. reported, “Breastfeeding has a larger impact on women’s health than previously appreciated” (Bartick et al. 2017).
American Academy of Pediatrics (2012). Committee on Nutrition, Section on Breastfeeding Policy Statement. Breastfeeding and the Use of Human Milk. Pediatrics, 129(3), e827-841, doi:10.1542/peds.2011-3552.
American Heart Association Utah Fact Sheet (2015). Retrieved from http://www.heart.org/idc/groups/heart-public/@wcm/@adv/documents/downloadable/ucm_493916.pdf. Accessed April 30, 2019.
Bartick, M. C. et al. (2017). Suboptimal breastfeeding in the United States: Maternal and pediatric health outcomes and costs. Matern Child Nutr, 13(1). doi:10.1111/mcn.12366.
Centers for Disease Control (2016) Breastfeeding Report Card. Retrieved from https://www.cdc.gov/breastfeeding/pdf/2016breastfeedingreportcard.pdf Accessed April 30, 2019.
Dermer, A. (2001). A Well-Kept Secret Breastfeeding’s Benefits to Mothers. New Beginnings 18(4) 124-127. Healthy People 2020. About Healthy People (2014). Retrieved from https://www.healthypeople.gov/2020/About-Healthy-People Accessed April 30, 2019.
Kelishadi, R. and Faraijan, S. (2014). The protective effects of breastfeeding on chronic non-communicable diseases in adulthood: A review of evidence. Adv Biomed Res, 3,3.
Schwarz, E. B., and Nothnagle, M. (2015). The Maternal Health Benefits of Breastfeeding. Amer Fam Phys 91(9), 603-604.
Victoria, C.G. et al. Lancet Breastfeeding Series Group (2016). Breastfeeding in the 21st century: epidemiology, mechanisms, and lifelong effect. Lancet, 387,475-490.
Wallenborn, J. T., Perera, R. A., and Masho, S. W. (2017). Breastfeeding after Gestational Diabetes: Does Perceived Benefits Mediate the Relationship? J of Pregnancy, 2017:9581796. Doi:10.1155/2017/9581796.
World Health Organization Noncommunicable Diseases Fact Sheet (2018). Retrieved from https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases Accessed April 30, 2019.
Lechtenberg E. (2019). Breastfeeding Protects Mothers. Utah Women’s Health Review. doi: 10.26054/0K8E5MVQR6.