Social Capital: A Remedy for Deaths of Despair in the Rust Belt US Counties?

doi:10.21203/rs.3.rs-4532220/v1

Download PDF

Research Article

Social Capital: A Remedy for Deaths of Despair in the Rust Belt US Counties?

https://doi.org/10.21203/rs.3.rs-4532220/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

This study emphasizes how crucial social capital to decrease the deaths of despair among Rust Belt counties. From the year 2015 the social theory of “deaths of despair” became a matter of curiosity among researchers: rising despair and unemployment in regions like the Rust Belt were the common cause of rising death rates among white Americans. Suicide, alcoholic liver disease, and drug overdose are the three categories of disease. The Appalachian region of the United States, particularly Pennsylvania, West Virginia, along with Delaware, has a high rate of diseases of despair and the deaths that follow. Numerous things, such as hopelessness, loneliness, loss, or a lack of direction or purpose in life, can contribute to despair. When researchers test the validity of this hypothesis, mixed results have been found in this regard.

Findings from 140 counties from the Rust Belt region revealed that social capital can be an effective policy instrument to decrease the deaths of despair. Therefore federal, state, county, academia and community leaders should implement policies to increase the social capital levels among US citizens.

JEL Codes: H10, H75, I15, I18

Social capital

loneliness

deaths of despair

rust belt

public policy.

There is a deadly drug epidemic in the United States right now. Between 1999 and 2016, the number of drug-related deaths in the United States increased from 16,849 to 63,632 (Hedegaard et al., 2017).

Downward intergenerational mobility, income stagnation, and broken social and family relations are the main components of what Case and Deaton refer to as cumulative disadvantage, according to their preliminary explanatory framework (King et al., 2022).

The economists Case and Deaton revealed in 2015 that middle-aged non-Hispanic White people with low levels of education were experiencing an increase in premature mortality, and that decades-long achieves in US life expectancy had stopped and even reversed. They proposed that the rise in cause-specific mortality from drug overdoses, alcohol liver disease, and suicides was the cause of this premature mortality. They further proposed that hopelessness brought on by unfavorable social and economic conditions was the root cause of these increases in cause-specific mortality. It gave rise to the widely accepted narrative of people dying of despair (Shanahan and Copeland, 2021).

Suicide, drug poisoning, and alcohol-related deaths have all increased, contributing to the US's declining life expectancy. To guide public health initiatives, it is necessary to determine whether or not patterns associated with these causes differ (Shiels et al., 2020). A systematic review (Vowles et al., 2015) discovered that in the US, between 21 and 29 percent of patients who are prescribed opioids over chronic pain abuse them. Evidence that prescription opioid abuse is causally linked to a higher risk of heroin use in adolescence was also discovered by a novel longitudinal study (Kelley-Quon et al., 2019).

In the United States, drug poisonings, alcohol-related causes, and suicide have all seen sharp increases in death rates, with middle-aged White, American Indian, and Alaska Native men as well as women experiencing the greatest increases (Shiels et al., 2017; Case & Deaton, 2015; 2017; Stein et al., 2017; Woolf et al., 2018).

Between 2015 to 2017, there were yearly decreases in the US life expectancy due to increases in midlife mortality (Kochanek et al., 2017; Murphy et al., 2018; Xu et al., 2015).

It has been proposed that rising rates of unemployment and financial instability are societal factors at the core of these increases (Case & Deaton, 2017).

Among Black and Latino people, premature mortality decreased from 2000–03 to 2012–15, while among White people, it increased in many US counties. Nationwide, the death rate from drug poisoning rose in every county. Between 2000 and 2015, white individuals aged 25 to 64 showed significant increases in both urban and rural counties, regardless of their socioeconomic status (Shiels et al., 2019).

There have been documented notable increases in alcohol-related deaths in the US during the previous 20 years. Comprehensive evaluations of the patterns in alcohol-related mortality by age, sex, race/ethnicity, along with social and geographic variables are, however, absent (Spillane et al., 2020).

Landberg (2008) discovered that in Eastern European spirit-consuming nations (Poland, Belarus, and Russia), an increase in the average person's alcohol intake of 1 liter was linked to a 5.7–7.5% rise in overall suicide rates. Accidents and liver disorders are also closely associated with excessive alcohol consumption, particularly risky binge drinking. Additionally, there is a direct correlation between stress and hopelessness and suicide and cardiovascular illnesses (Razvodovsky, 2013; Brainerd, 2001). After state socialism collapsed, drug abuse also skyrocketed in Eastern Europe, although its overall impact on the mortality rate crisis is negligible (King et al., 2022). According to King et al. (2009), they also discovered that privatization was linked to deaths, mostly of working-age men, and that it also predicted alcohol use, suicide, being unemployed, and acute heart disease. The loss of nearly two years of life expectancy for men and 0.7 years for women was linked, according to the authors, to extreme privatization policies. Furthermore, (King et al., 2022) radical privatization was equivalent to depriving these workers of their de facto property rights, which Soviet-style companies granted to their workers. This greatly increased stress and uncertainty. Along with many other social benefits, these companies gave their workers a sense of purpose and belonging. All of these were compromised by privatization.

The author, Rozalina McCoy, M.D., a primary care physician and endocrinologist, pointed out that in 2020, COVID-19 was either the cause or a contributing factor in nearly 10% of all deaths in Minnesota. One of the main causes of these deaths, particularly for older adults living in rural areas, was social isolation (Jacobbi, 2023)

Although loneliness is not new, there seems to be a growing awareness of it in terms of social and health issues. In 2018 and 2021, the UK and Japan, respectively, appointed ministers of loneliness (Lancet, 2023). Standardized and approved measuring instruments should be used to include loneliness in general health surveillance that covers a wider range of age and geographic areas (Surkalim et al., 2022).

While not exclusive to the US, these health catastrophes are uncommon. An unparalleled mortality crisis struck Eastern Europe thirty years ago as former socialist nations made the shift to capitalism, foreshadowing the epidemic of deaths from despair that is plaguing the region today (Eberstadt, 2010).

The relationship between social capital, health, and well-being has garnered attention recently, and the idea of social capital has grown in significance in public health research and health promotion (Putnam, 2000; Islam et al., 2006).

In the 21st century, self-harm and substance use disorders are becoming increasingly common causes of death by despair for people at the bottom of the social hierarchy. This is a hallmark of American society. Depressing deaths are largely caused by socioeconomic disruptions, which also influence other primary causes of health disparities and healthcare behavior (King et al., 2022).

The United States was already dealing alongside a crisis of hopelessness and deaths from alcohol poisoning, overdoses, and suicides when the COVID pandemic struck, shocking society in a way never seen before. Two conclusions are highlighted by our results: Because results from different datasets can differ significantly, researchers looking into trends in behavioral and mental wellness should exercise caution when relying excessively on one. Ans, years later, there may be a correlation between higher rates of overdose and suicide in metropolitan areas with high rates of anxiety and depression (Dobson et al., 2022).

By 2015, US life expectancy stopped, may be caused by the high death rate among manual laborers from drug and alcohol abuse as well as suicide. The phrase "deaths of despair" was first used by economists Angus Deaton and Anne Case to describe a growing health crisis among the poorest segments of the American population. They calculate that from the turn of the century, over half a million unnecessary deaths have resulted from such despair, which is rooted in strong social convulsions caused by rapid declines in industry (Case & Deaton 2020).

In the US, up until 2018–19, patterns in deaths from despair were stable and showed that White people with less education had higher rates of despair and mortality, while low-income minorities had lower rates of these deaths and high levels of optimism (Graham & Pinto 2019).

The United States is seeing an increase in midlife non-Hispanic white mortality, especially in small metro along with rural counties (Parsons & Barger, 2019).

Between 2001 and 2016, there was a significant increase in DoD mortality within England and Wales, with male rates consistently higher than female rates. The increase in drug-related fatalities is the main cause of the rise. Suicide, alcohol-related deaths, and drug poisoning all showed increases during this time period, but at the national level, their trends did not tightly coincide (Augarde et al., 2022).

Mortality rates in Scotland are higher than in other nations of Western Europe, even after deprivation is taken into consideration. This "excess" mortality is a result of higher rates of violence, suicide, and drug- and alcohol-related deaths (DRDs), especially in young adults. The recent increases in alcohol-related deaths along with suicide can be explained by age-period and cohort effects, respectively (Parkinson et al., 2018).

The public health research has addressed the issue of ignoring the burden of mortality related to mental health issues extensively. To enhance policy and gain a deeper understanding of national and international mental health issues, pertinent scientific data from the societies with the highest rates of mental health death are crucial. Three Baltic States—Estonia, Lithuania, and Latvia—are nations in Central and Eastern Europe that have had severe trauma following the Soviet transition and have some of the highest rates of alcohol-related and suicide-related deaths in the continent. When estimating the overall burden of mortality related to mental health issues, the Baltic States along with other post-soviet nations should take into account the proportions of different external factors of death as well as alcohol-related reasons of death (Stumbrys et al., 2022).

Apart from the COVID-19 patients' illnesses, social distancing measures, mandatory lockdowns, and a variety of psychosocial factors have caused mental health issues for isolated individuals and the general public. During the pandemic, the incidence of anxiety and depression has increased significantly (Zhu et al., 2023). According to Zhou et al., during the COVID-19 outbreak, the prevalence of anxiety and depression symptoms within Chinese high school students was 37.4% and 43.7%, respectively (Zhu et al., 2020). Older adults (over 50) were identified as another group susceptible for mental health issues in a different study (Tian et al., 2020) presumably as a result of ageism, inactivity, and loneliness (Creese et al., 2021; Bergman et al., 2020).

In India's northeastern state and eastern state of West Bengal, the study examines the relationship between the substance use within scheduled tribe men—who are primarily recognized for their primitivism, isolation, insecurity, and social, educational, as well as economic regression—and non-scheduled tribe men. Middle-aged men who work in unorganized jobs, practice different religions, come from lower socioeconomic quintiles, have been divorced, separated, abandoned, or widowed have significantly higher rates of substance use, according to a study that correlated substance use with socioeconomic characteristics (Barman & Chowdhury, 2023).

Suicide is the third most common cause of death in the United States and the fourth most common cause of death for young people globally (Hughes et al., 2023).

The year 2020 saw suicide account for almost 20 percent of all youth fatalities in the US (CDC, 2023). Although the full impact of the COVID-19 pandemic on youth suicide is still unknown, preliminary data indicate that the US suicide rate is generally rising, with young people from minority groups suffering a disproportionate share of the increase (Curtin et al., 2022).

Before the pandemic, young people and children in the UK had declining mental health, and the social, educational, and health outcomes for kids with mental health disorders are worse than they were for earlier generations (Sellers et al., 2019). Anxiety, depression, as well as self-harm increased between 2004 and 2017, especially in adolescent girls (Sadler et al., 2017). Whether or not there is a pandemic, people who are most at risk of experiencing poor mental health outcomes need to have access to preventive mental health interventions (Hjorthøj & Madsen, 2023).

There is still much to learn about the factors preventing youth suicide. Strong interpersonal relationships, faith/spiritual factors, family cohesion, improved access to care, cognitive flexibility, and emotion regulation abilities have all been linked to preventing suicidal behavior within young people (Abraham & Sher, 2017; Droege et al., 2017; Robinson et al., 2022; Dorol-Beauroy-Eustache & Mishara, 2021; Allen et al., 2022). While some negative aspects of social media and the internet have raised concerns, some positive aspects, like community, connection, and decreased isolation, may actually be protective (Marchant et al., 2017). The evaluation of social connectedness to be a potential target for clinical risk assessment and suicide prevention tactics is becoming more prevalent (King et al., 2019). The correlation between suicidality and intersecting marginalized identities was considerably lowered by family support, highlighting a possible area for intervention (Hughes et al., 2023).

The epidemic of depressive deaths can be linked to modern globalization in many cases. Remarkably, marginalized as well as indebted farmers in India have one of the highest rates of suicide globally as a result of the agricultural sector's liberalization in the 1990s (Kennedy & King, 2014).

According to a report by the US National Academy of Sciences, mortality is declining in 16 developed countries (Western Europe, Canada, Australia, as well as Japan). It has been noted that humans are limited by evolutionary strategy in requiring social support throughout their entire life cycle. When there is no support, problems mount and it appears that there is no way out. The sixteen wealthy nations offer collective support at every level, thereby enabling multiple routes forward and shielding people and families from hopelessness. By using the 16-nation control group's best practices, the US could resolve its health crisis (Sterling & Platt, 2022).

The United States has experienced a rise in mortality rates, which can be attributed in part to an increase in alcohol and drug poisoning, suicide, and heart disease as a result of increasing obesity.Deaths from despair are mostly caused by isolation on the rise and attempts by individuals to self-medicate in order to make up for dopamine deficiency in the brain (Freeborn, 2022).

Perlman and Peplau (1982) define loneliness as an individual's desired as well as achieved degrees of social relations not matching, which leads to a subjective, unpleasant, along with distressing phenomenon. Therefore, it is possible to argue that loneliness results from a sense of a mismatch between one's desired degree and/or quality of relationships and those that actually exist. Loneliness, or the lack of it, is frequently used to indicate mental well-being in correlation with mental health measures, particularly in older adults (Luanaigh & Lawlor, 2008).

The majority of studies concentrate on the elderly, so (Mansfield et al., 2019) suggest doing research that looks at a larger range of age groups in various social contexts and/or that takes a defined life course perspective. According to some philosophers, loneliness is a common human experience (Rotenberg, 1999; Mijuskovic, 1981).

In their definition of connectedness, it means a feeling that arises from safe and enduring relationships throughout families, schools, and communities—a sense of being looked after, supported, belonging, and close to others (DiClemente et al., 2009).

Similarly, the Harvard Study of Adult Development found that individuals with strong ties to their family, community, and school outlive, are healthier, happier, and live longer than their less connected peers, based on a 70-year follow-up of over 700 men. A happier, healthier life is facilitated by relationships in all of their forms, including those found in book clubs, Bible study groups, families, coworkers, romantic partnerships, and tennis partners (Waldinger & Schulz, 2023).

The data revealed three different but related conceptualizations of loneliness: existential, emotional, and social. The results will be helpful in public policy as well as practice decision-making that aims to determine who experiences loneliness, why it happens, how to deal with it, and the best strategies for minimizing loneliness or maximizing its benefits for better wellness and health outcomes. In our review, social loneliness was the main topic of most studies (Mansfield et al., 2021).

Table 1

Parts of loneliness
Loneliness
• emotional loneliness
• social loneliness
• existential loneliness
Source: Mansfield et al., 2019

Loneliness is a topic that has gained attention due to the COVID-19 pandemic, which has forced many people to rearrange their work schedules and require physical distance during certain times. There's no denying the health risks. An increased risk of infectious diseases, diabetes, hypertension, heart disease, depression, and anxiety is linked to a lack of social connections. A meta-analysis of data coming from 113 nations (Surkalim et al., 2022) demonstrates that loneliness has become a global problem, with a significant fraction of the population experiencing problematic degrees of loneliness in many of these nations. In addition, it is false to believe that social isolation and loneliness are primarily problems for the elderly; loneliness impacts people of every age, and understanding and treating it requires a life-course approach. With possible long-term effects on mental and physical wellbeing, adolescents and young adults—for whom socialization is such an important aspect of development—may be especially vulnerable (The Lancet, 2023).

United States Surgeon General Dr. Vivek Murthy states that, an older adult's chance of developing dementia is increased by 50%, heart disease is increased by 29%, and stroke is increased by 32% as a result of poor or inadequate social connection. In addition, there is a greater than 60% chance of premature death when one is socially isolated. Isolation and loneliness have a significant negative impact on our mental health along with to our physical health. To properly address the crisis of mental health in America, it is imperative to address loneliness and isolation, as over one in five adults and one in three young people in the country suffer from a mental illness. An, overlooked remedy for the pervasive epidemic of loneliness and isolation, which negatively impacts both our personal and societal health and well-being, is social connection. In addition to being good for one's own health, social interaction strengthens communities. Research suggests that stronger ties can lower the risk of developing major illnesses like depression, heart disease, stroke, and dementia. Communities with stronger social ties perform better on a number of indicators, including civic engagement, prosperity, population health, safety, and resilience in the face of natural disasters (HHS, 2023).

Social wellbeing is fundamentally based on meaningful social relationships. The gap between one's ideal and real social connections is known as loneliness, and it has been connected to a number of negative health effects, including heart disease (Hodgson et al., 2020), cognitive decline (Lara et al., 2019) as well as premature death (Holt-Lunstad et al., 2015).

Over the past 20 years, there has been an increase in deaths from despair, including suicide, drug and alcohol overdoses, chronic liver disease, and cirrhosis (Steelesmith et al., 2023).

In the US, the death rates from poisonings, guns, along with other injuries rose significantly between 1999 and 2020. The sharp rise in accidental poisoning and gun-related killings is a national emergency necessitating immediate local and federal public health responses (Lawrence et al., 2023).

Most countries' data indicate that experiencing problematic loneliness is not unusual. Furthermore, data gaps concerning country income groups and geographic regions are evident. Social wellbeing is frequently measured and tracked in Europe; abundant information for Europeans of all ages has been made available by a number of sizable multi-country surveys. In contrast, the majority of low- and middle-income countries lack data or have insufficient amounts of it. Thirdly, there were significant regional and national differences in the prevalence of loneliness. Although loneliness was once thought to be an individual problem, notable researchers and US Surgeon General Vivek Murthy have recently pushed for the treatment of loneliness as a major public health concern and as a "epidemic." Our observations of the observable differences in loneliness prevalence between nations further support the theory that a variety of macro factors, including social security, welfare, demographics, economic status, and inequality, have an impact on how severe loneliness is. Poverty, inequality, and culture are just a few of the social and structural elements that contribute to loneliness as a systemic issue (Ding et al., 2022).

A recent study for Japan comprised 27,520 community-dwelling individuals in total. In the adjusted model, there was no significant difference between living conditions and loneliness; however, living in a deprived area was associated with higher levels of loneliness. Living in a higher level of urbanization and lower deprivation was associated with a higher score for social isolation. The adjusted model revealed a significant group difference (p < 0.001) in social isolation. The living situation had minimal overall effects on social isolation and loneliness (Sasaki et al., 2023).

According to a nationwide longitudinal study conducted in Singapore, approximately 23.0% of senior citizens experienced chronic loneliness (Lim & Chan, 2017).

Previous results from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) showed that loneliness affected roughly 30.6% of older women and 22.9% of older men (Zhou et al., 2019).

The foundation of health and well-being is connection to others, and the relationships that adolescents have with their family, friends, and community possess a significant impact on their development (Petrosino et al., 2013).

A vital component of healthy development is connectivity. Research indicates that effective initiatives seek to improve relationships with peers, parents, schools, and the community (Blum et al., 2022).

Adolescents with at least one parent have fewer emotional difficulties than their less connected peers (Ungar, 2014), fewer attempts at suicide (Kuramoto-Crawford et al., 2017), fewer behavioral issues and improved achievement in school (Gonzalez-DeHass et al., 2005), reduced involvement in violence and increased self-esteem (Farrell et al., 2010), and drug abuse (Wills & Yaeger, 2003).

According to neurodevelopmental (Albert et al., 2013) research, peer pressure has a tendency to have a bigger impact on behavior in younger people than in older people (14–18 years old).

When compared to more solitary individuals of the same age, young people with strong peer relationships perform better socially and emotionally (Oldfield et al., 2016).

A young person's behavior and general well-being are significantly influenced by the neighborhood in which they reside. Empirical studies have consistently demonstrated that in environments characterised by social cohesion, youth are less likely to participate in high-risk behaviors and endure emotional distress (Borowsky et al., 1999; Youngblade et al., 2007), and are more likely to exhibit elevated levels of self-efficacy and positive health behaviors (DeLuca et al., 2016). To express similar ideas, authors employ a variety of terminology. Some writers discuss, for instance, the idea that a community can effect change or what is known as community self-efficacy (Tadaka et al., 2016). Another aspect of community connectedness that is discussed by other researchers is social capital. Putnam (2018) outlines several examples of social capital, including involvement in public affairs, volunteerism in the community, informal sociability, and organizational life within the community.

Adolescent wellbeing has been demonstrated to be impacted by digital and social media use in both positive and negative ways (Yau and Reich, 2018). But digital and online connections by themselves can never fully replace face-to-face relationships (Twenge et al., 2021). The Programme for International Student Assessment (PISA) data from 37 countries was used in a large study on teenage loneliness from 2012 to 2018, and the results showed that loneliness increased in all but one of the countries. More than one million 15 and 16-year-olds participated in the study, which discovered a link between smart phone and internet use and loneliness (Jose et al., 2012).

According to studies, loneliness is a detrimental emotional state that can deteriorate an older person's health and well-being (Hawkley and Cacioppo, 2010; Luhmann and Hawkley, 2016; Lim & Chan, 2017). For instance, it's been discovered that loneliness increases the risk of stroke and coronary heart disease (Valtorta et al., 2016), as well as dementia (Holwerda et al., 2014), resulting in a lower standard of living (Luo et al., 2012).

Bourdieu (1986) was the first to propose social capital. Putnam (1994) along with Coleman (1990), two of the definitions of social capital that are most frequently used, define social capital as the characteristics of social organizations, such as social networks, norms, as well as trust, that can increase social efficiency by encouraging coordinated actions.

Across all social science disciplines, the idea of social capital—here defined as the norms as well as networks that allow people to act collectively—saw a remarkable surge in popularity in the 1990s. The four main approaches that social capital research has taken are communitarian, the networks, institutional, and synergistic. The authors also chart the evolution of social capital studies in relation to economic development. Based on available data, it appears that the synergy view—which recognizes both the positive and negative effects that social capital can produce and emphasizes incorporating various levels along with dimensions of social capital—has the most empirical support out of the four perspectives. It also best supports comprehensive and cogent policy recommendations (Woolcock & Narayan, 2000).

We all know by now how important social capital is to sustainable development. The importance of institutions, the networks, and the norms and values that support them for the accomplishment of development interventions has been shown by researchers in anthropology sociologists and political scientists, as well as economists in different contexts (Grootaert & Van Bastelar, 2002).

Although it is commonly acknowledged that social capital is one of the few types of capital accessible to the impoverished, little is known about the mechanisms through which development policies influence the formation of that social capital (Fox & Gershman, 2000).

An enormous amount of human capital has been amassed this century. The way that the economic actors engage as well as organize themselves to create growth and development is something that all three of these kinds of capital have now come to realize, and as a result, they only partially determine the course of economic growth. Social capital is the component that's missing (Grootaert, 1998).

The term social capital has swiftly become widely used in our conversations regarding the "connectedness" of individuals to their communities. Nonetheless, it continues to be a difficult concept to define (Dasgupta & Serageldin, 1999).

Social capital is frequently obtained through employment and university education in high-income nations. But family can also be a source of social capital (Addae, 2020) in addition to neighborhood and community involvement (Blum et al., 2022). The World Bank has demonstrated time and time again how human networks formed through social capital maximize personal financial resources, thereby amplifying the effects of financial capital (Grootaert, 1998).

The term "social capital" describes a set of social relationships that can be developed through mutually beneficial interactions throughout a neighborhood, community, and society, either on an individual or collective level (Nyqvist et al., 2016; Putnam, 2000; Coll-Planas et al., 2017).

Falling social capital is another sign of social disintegration that contributes to deaths of despair, as also mentioned by Case and Deaton (2020). Kennedy et al. (1998) discovered significant correlations between life expectancy and social capital indicators as well as mortality rates utilizing nationally representative survey information on households from 40 regions of Russia.

Putnam (2000) argues that engaging in social activities and having trust for other people improves interpersonal relationships, which is advantageous for those who live in a neighborhood, community, or society (Nyqvist et al., 2016).

The majority of researchers agree that social capital has both collective as well as individual dimensions (Putnam, 2000) and can be defined as a social resource (Schuller et al., 2000).

Social capital explains a significant portion of the variation in health, as Rose (2000) found in a nationally representative sample of adult Russians. Skrabski et al. (2003) also discovered a strong correlation between the a lower level of social capital, mistrust, as well as mortality using data from 20 counties in Hungary in 1995.

To connect macrochange to individual health behavior, sociological concepts like fatalism, alienation, anomie, and social disintegration (the loss of social capital) should be used more often (King et al., 2022).

The majority of earlier research on loneliness has been done in order to identify risk factors in particular age groups, such as youth or the elderly. Less research has been done on the relationship between loneliness and social capital in varying age cohorts. This study set out to investigate, in a Finnish context, the relationship among social capital and loneliness experiences across various age groups. In comparison to older people (27.3%), younger people (39.5%) reported feeling lonely more frequently, which is defined as occasionally or often. Within all four age groups, low trust was associated with loneliness. For every age group, there was a different correlation between loneliness and other components of social capital. Among adults in general, frequent loneliness was common and may be considered a public health concern. Our results suggest that loneliness may be predisposed to by low social capital, particularly low trust (Nyqvist et al., 2016).

Moreover, being a widow or living alone are recognized social indicators for loneliness in older adults (Pinquart and Sörensen, 2003). As people age, loneliness increases, especially for the oldest elderly, who account for up to 50% of cases of serious or mild loneliness (Dykstra, 2009).

While older people's satisfaction via support is crucial, loneliness in young people seems to be more influenced by the amount of supportive peers within their network (Kafetsios and Sideridis, 2006). According to earlier studies, loneliness is also prevalent in young people; in early adulthood, 15–30% of people report feeling lonely to some extent, while loneliness is less common in middle age (Yang & Victor, 2011).

The importance and applicability of social resources, particularly social capital, in preserving the health and well-being of older adults have been highlighted with the growth of the determinants of health (Chen et al., 2014).

An increasing body of research has shown a relationship between older people's health and well-being and social capital (Tomioka et al., 2017).

Social capital is one of the established social risk variables for loneliness. Previous studies have shown that loneliness is negatively correlated with interpersonal and social trust and also a sense of belonging in both younger and older adults (Rotenberg et al., 2010; Tomaka et al., 2006; Imamura et al., 2016), and numerous research, including those from China, have looked at the connection between loneliness and social capital (Nyqvist et al., 2016; Niedzwiedz et al., 2016; Jiang et al., 2020).

Bai et al., (2021) in their research to investigate the relationship in Anhui Province, China, between social capital along with loneliness, results demonstrate the relationship between loneliness within older adults and social capital. This suggests that social capital may play a major role in reducing loneliness in later life, particularly in regards to trust, social connection, as well as social participation.

A low degree of social capital was one of the many factors that contributed to loneliness in later life (Cohen-Mansfield et al., 2016). A more thorough examination of the social capital revealed a correlation between high levels of loneliness within adults residing in both community homes and nursing homes with low quantities of social support, trust, and cohesiveness. Among senior citizens who resided in community housing, social connection and loneliness had a negative correlation. Loneliness was found to be strongly impacted by institutionalization (Chen et al., 2023).

However, previous studies examining the connection between loneliness and social capital in older populations measured social capital using a variety of factors and produced inconsistent results (Bai et al., 2021). In a study spanning 14 European nations, social capital—which includes regular social interaction—was associated with a lower incidence of loneliness as well as a lessening of its effects on low-income families (Niedzwiedz et al., 2016). An earlier study among older Chinese rural widows found that social capital—both bridging and bonding social capital—was linked to loneliness (Jiang et al., 2020).

Nyqvist et al., (2021) examine the relationship between two widely-used dimensions of social capital—structural and cognitive—and the absence of loneliness by examining data from the European Social Survey (ESS) for five distinct welfare states. Authors concentrate on two time periods: pre- and post-Global Financial Crisis (2008–2009). Based on their analysis, it appears that the five welfare regimes differ in terms of social capital, loneliness, and social contacts and trust. While social trust along with loneliness showed mixed results, a negative trend in social contacts was noted. Lack of loneliness was linked to social capital, though the relationship varied depending on the welfare system. The results are examined in the context of welfare state regimes

In this study, I conducted an cross-section empirical analysis of the impact of social capital, median household income, adults with frequent mental distress on deaths of despair. To do this, I used secondary data collected from the The Healthiest Communities Data Explorer, specifically 140 selected US counties which located in Rust Belt. covering the year 2022. Later, in the discussion, I carried out a comparison of the results. To do this, I used the STATA 14.2 econometric application and MS Excel software products.

Dependent variable: dod

Deaths of despair (number/100K)

Independent variables: medinc, men, sc

median household income (US Dollars, 2022)

adults with frequent mental distress (%)

social capital (score)

The baseline model that I adopt for the empirical analysis is specified in Eq. (1).

dod _𝑖𝑡 = β₀ + β₁medinc_𝑖𝑡+ 𝛽₂men_𝑖𝑡 + 𝛽₃sc_𝑖𝑡 + 𝜀_𝑖𝑡 (1)

Research Question (RQ): What effect do median household income, adults with frequent mental distress and social capital, have on deaths of despair in selected US counties?

The first explanatory variable included in the model is median household income which is expected to be negatively related to the dependent variable. The second variable I have included as a regressor in the estimated equation is adults with frequent mental distress, which is expected to have a positive relationship with deaths of despair. The third variable that I have included as a regressor is the social capital, an increase in the social capital is expected to decrease deaths of despair.

Figure 1. depicts the relationship between social capital and death of despair regarding to 140 selected US counties which are located in the Rust Belt region. As seen from the figure, when scores of the social capital increases the death of despair (number/100K) decreases accordingly.

Table 2

Regression model for the variables included in the econometric model
lndod	Coef.	Std. Err.	t	P>\|t\|	95% Conf. Interval
lnmedinc	− .3055157	.1986427	-1.54	0.126	− .6983699 .0873385
lnmen	1.063895	.2062539	5.16	0.000	.6559886 1.471802
lnsc	− .2377071	.1270478	-1.87	0.064	− .4889684 .0135543
_cons	5.211768	2.582326	2.02	0.046	.1047224 10.31881

Table 3

Endogeneity test for the variables included in the econometric model
lndod	Coef.	Robust Std. Err.	t	P>\|t\|	95% Conf. Interval
lnmedinc	− .3055157	.2071784	-1.47	0.143	− .7152508 .1042193
lnmen	1.063895	.1985935	5.36	0.000	.6711386 1.456652
lnsc	− .2377071	.1008806	-2.36	0.020	− .4372179 − .0381963
_cons	5.211768	2.611532	2.00	0.048	.0469612 10.37658

β₀ - if lnmedinc, lnmen and lnsc are constant (X₁, X₂, X₃ = 0), then lndod will be 5.211768 units (P- value < 0.05).

β₁ - if lnmedinc increases by one unit, then lndod will decrease by 0.3055157 units. (P-value > 0.05).

β2 - if lnmen increases by one unit, then lndod will increase by 1.063895 units (P-value < 0.05).

β3 - if lnsc increases by one unit, then lndod will decrease by 0.2377071 units (P-value < 0.05)

The foundation of healthy development is connectedness (Blum et al., 2022). Researchers can gain a better understanding of the effects of residential differences on psychological well-being and mental health by utilizing social capital theory (Nummela et al., 2009).

After conducting a cross-section analysis of 140 selected US counties which are located in Rust Belt region; when social capital increases 1 unit, deaths of despair decreases 0.2377 units with the corresponding p value of 0.020 and significant.

In order to decrease the numbers of deaths of despair at federal, state, county and community level policies regarding to increase connectedness, trust and civil engagement activities should take into consideration. The increase in median income only can not solve the loneleness epidemic among individuals. Therefore to invest in social capital could a tool to solve this social epidemic.

Abraham, Z.K., & Sher L. (2017). Adolescent suicide as a global public health issue. Int J Adolesc Med Health;31.pmid:28686572
Addae, E.A. (2020). The mediating role of social capital in the relationship between socioeconomic status and adolescent wellbeing: evidence from Ghana. BMC Public Health;20: 20. https://doi.org.10.1186/s12889-019-8142-x pmid:31910835
Albert, D., Chein, J., & Steinberg, L. (2013). Peer influences on adolescent decision making. Curr Dir Psychol Sci; 22:114-20.pmid:25544805
Allen, J., Wexler, L., Rasmus, S. (2022). Protective Factors as a Unifying Framework for Strength-Based Intervention and Culturally Responsive American Indian and Alaska Native Suicide Prevention. Prev Sci; 23:59-72. doi:10.1007/s11121-021-01265-0 pmid:34169406
Augarde, E., Gunnell, D., & Mars, B. et al. (2022). An ecological study of temporal trends in ‘deaths of despair’ in England and Wales. Soc Psychiatry Psychiatr Epidemiol 57, 1135–1144. https://doi.org/10.1007/s00127-022-02251-9
Bai, Z., Wang, Z., Shao, T. et al. (2021). Association between social capital and loneliness among older adults: a cross-sectional study in Anhui Province, China. BMC Geriatr 21, 26. https://doi.org/10.1186/s12877-020-01973-2
Barman, M., Chowdhury, I. R. (2023). Substance Uses and Associated Sociodemographic Factors Among Male Tribes and Non-Tribal Communities of Eastern and North Eastern States in India: An Evidence-Based Study from the National Family Health Survey-5. Glob Soc Welf https://doi.org/10.1007/s40609-023-00328-0
Bergman, Y.S., Cohen-Fridel, S., Shrira, A., Bodner, E., & Palgi, Y. (2020). COVID-19 health worries and anxiety symptoms among older adults: The moderating role of ageism. Int Psychogeriatr, 32: 1371–1375.
Blum, R. W., Lai, J., Martinez, M., & Jessee, C. (2022). Adolescent connectedness: cornerstone for health and wellbeing BMJ; 379 :e069213 doi:10.1136/bmj-2021-069213
Borowsky, I.W., Resnick, M.D., Ireland, M., & Blum, R.W. (1999). Suicide attempts among American Indian and Alaska Native youth: risk and protective factors. Arch Pediatr Adolesc Med;153:573-80. doi:10.1001/archpedi.153.6.573 pmid:10357296
Bourdieu, P. (1986). Handbook of theory and research for the sociology of education. New York: Greenwood Press;
Brainerd, E. (2001). Economic reform and mortality in the former Soviet Union: a study of the suicide epidemic in the 1990s. Eur. Econ. Rev. 45(4–6):1007–19
Case, A., & Deaton, A. (2015). Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century. Proc Natl Acad Sci U S A.;112(49):15078-15083. doi: 10.1073/pnas.1518393112
Case, A., & Deaton, A. (2017). Mortality and morbidity in the 21^st century. Brookings Pap Econ Act.:397-476. doi: 10.1353/eca.2017.0005
Case, A., & Deaton, A. (2020). Deaths of Despair and the Future of Capitalism. Princeton University Press.
CDC (2023). Centers for Disease Control and Prevention. Fatal Injury and Violence Data. https://www.cdc.gov/injury/wisqars/fatal.html.
Chen, Y., Hicks, A., & While, A. E. (2014). Loneliness and social support of older people in China: a systematic literature review. Health Soc Care Community;22(2):113–23.
Chen, Y., Zhou, Y., Li, M., Hong, Y., Chen, H., Zhu, S., Zhou, Y., Yang, S., Wu, X., & Wang, D. (2023). Social capital and loneliness among older adults in community dwellings and nursing homes in Zhejiang Province of China. Front Public Health. May 19;11:1150310. doi: 10.3389/fpubh.2023.1150310. PMID: 37275480; PMCID: PMC10237354.
Cohen-Mansfield, J., Hazan, H., Lerman, Y., & Shalom. V. (2016). Correlates and predictors of loneliness in older-adults: a review of quantitative results informed by qualitative insights. Int Psychogeriatr.;28(4):557–76.
Coleman, J. S. (1994). Foundations of social theory. Harvard University press.
Coll-Planas, L., Nyqvist, F., Puig, T., Urrútia, G., Solà, I., & Monteserín, R. (2017). Social capital interventions targeting older people and their impact on health: a systematic review. J Epidemiol Community Health;71(7):663–72.
Creese, B., Khan, Z., Henley, W., O'Dwyer, S., Corbett, A., Vasconcelos, Da Silva M, et al. (2021). Loneliness, physical activity, and mental health during COVID-19: A longitudinal analysis of depression and anxiety in adults over the age of 50 between 2015 and 2020. Int Psychogeriatr, 33: 505–514.
Curtin, S., Garnett, M., & Ahmad, F. (2022). Provisional numbers and rates of suicide by month and demographic characteristics: United States, 2021. https://stacks.cdc.gov/view/cdc/120830.
Dasgupta, P., & Serageldin, I. (Eds.). (1999). Social capital: a multifaceted perspective. World Bank Publications. https://doi.org/10.1596/0-8213-4562-1
DeLuca, S., Clampet-Lundquist, S., Edin, K. (2016). Coming of age in the other America.Russell Sage Foundation.
DiClemente, R.J., Santelli, J.S., Crosby, R.A., Bernat, D.H., & Resnick, M.D. (2009). Connectedness in the lives of adolescents. In: DiClemente RJ, Santelli JS, Crosby RA, eds. Adolescent health: understanding and preventing risk behaviors.Jossey-Bass: 375-99.
Ding, D., Eres, R., & Surkalim, D. L. (2022). A lonely planet: time to tackle loneliness as a public health issue. BMJ, 377. https://doi.org/10.1136/bmj.o1464
Dobson, E., Graham, C., Hua, T., & Pinto, S. (2022). Despair and resilience in the US: Did the COVID pandemic worsen mental health outcomes?. Brookings Global Working Paper #171 Global Economy and Development program at Brookings www.brookings.edu/global
Dorol-Beauroy-Eustache, O., & Mishara, B.L. (2021). Systematic review of risk and protective factors for suicidal and self-harm behaviors among children and adolescents involved with cyberbullying. Prev Med; 152:106684. doi:10.1016/j.ypmed.2021.106684 pmid:34538376
Droege, J.R., Robinson, W.L., & Jason, L.A. (2017). Suicidality Protective Factors for African American Adolescents: A Systematic Review of the Research Literature. SOJ Nurs Health Care;3:310.15226/2471-6529/3/2/00130. doi:10.15226/2471-6529/3/2/00130 pmid:33344874
Dykstra, P. A. (2009). Older adult loneliness: myths and realities. Eur J Ageing.;6:91–101.
Eberstadt, N. (2010). The enigma of Russian mortality. Curr. History 109(729):288–94
Farrell, A.D, Mays, S., Bettencourt, A., Erwin, E. H, Vulin-Reynolds, M., Allison, K.W. (2010). Environmental influences on fighting versus nonviolent behavior in peer situations: a qualitative study with urban African American adolescents. Am J Community Psychol;46:19-35. doi:10.1007/s10464-010-9331-z pmid:20526663
Fox, J., & Gershman, J. (2000). The World Bank and social capital: Lessons from ten rural development projects in the Philippines and Mexico. Policy sciences, 33(3-4), 399-419.
Freeborn, J. (2022). 'Deaths of despair' on the rise in the US: Why here and not in other nations? https://www.medicalnewstoday.com/articles/deaths-of-despair-on-the-rise-in-the-us-why-here-and-not-in-other-nations
Gonzalez-DeHass, A.R., Willems, P.P., & Doan Holbein, M. F. (2005). Examining the relationship between parental involvement and student motivation. Educ Psychol Rev;(17):96-123doi:10.1007/s10648-005-3949-7.
Graham, C., & Pinto, S. (2019). Unequal Hopes and Lives in the U.S.A: Optimism, Race, Place, and Premature Mortality. Journal of Population Economics 32:665–733.
Gray, K. (2019). A conceptual review of loneliness across the adult life course (16+ years). University London.
Grootaert, C. (1998). Social capital: the missing link (English). Social Capital Initiative working paper series; no. 3 Washington, D.C.: World Bank Group. http://documents.worldbank.org/curated/en/902971468764409654/Social-capital-the-missing-link
Grootaert, C. & Van Bastelar, T. (2002). Understanding and Measuring Social Capital: A Multidisciplinary Tool for Practitioners. Directions in Development. Washington, DC: World Bank. http://hdl.handle.net/10986/14098
Hawkley, L. C., & Cacioppo, J.T. (2010). Loneliness matters: a theoretical and empirical review of consequences and mechanisms. Ann Behavior Med;40(2):218–27.
Hedegaard, H., Warner, M., & Miniño, A. M. (2017). Drug Overdose Deaths in the United States, 1999-2016. NCHS Data Brief, no. 294.
HHS (2023). New Surgeon General Advisory Raises Alarm about the Devastating Impact of the Epidemic of Loneliness and Isolation in the United States. https://www.hhs.gov/about/news/2023/05/03/new-surgeon-general-advisory-raises-alarm-about-devastating-impact-epidemic-loneliness-isolation-united-states.html
Hjorthøj, C., & Madsen, T. (2023). Mental health and the covid-19 pandemic BMJ; 380 :p435 doi:10.1136/bmj.p435
Hodgson, S., Watts, I., Fraser, S., Roderick, P., & Dambha-Miller, H. (2020). Loneliness, social isolation, cardiovascular disease and mortality: a synthesis of the literature and conceptual framework. J R Soc Med; 113:185-92. doi:10.1177/0141076820918236. pmid:32407646
Holt-Lunstad, J., Smith, T.B., Baker, M., Harris, T., & Stephenson, D. (2015). Loneliness and social isolation as risk factors for mortality: a meta-analytic review. Perspect Psychol Sci:10:227-37. doi:10.1177/1745691614568352. pmid:25910392
Holwerda, T. J., Deeg, D.J., Beekman, A.T, van Tilburg, T.G., Stek, M.L, Jonker, C, et al. (2014). Feelings of loneliness, but not social isolation, predict dementia onset: results from the Amsterdam study of the elderly (AMSTEL). J Neurol Neurosurg Psychiatry.;85(2):135–42.
Hughes, J, L, Horowitz, L. M., Ackerman, J. P, Adrian, M. C., Campo, J. V., Bridge, J. A. et al. (2023). Suicide in young people: screening, risk assessment, and intervention BMJ; 381 :e070630 doi:10.1136/bmj-2022-070630
Imamura, H., Hamano, T., Michikawa, T., Takeda-Imai, F., Nakamura, T., Takebayashi, T., et al. (2016). Relationships of community and individual level social capital with activities of daily living and death by gender. Int J Environ Res Public Health;13(9):860.
Islam, M. K., Merlo, J., Kawachi, I., Lindström, M., & Gerdtham, U. (2006). Social capital and health: Does egalitarianism matter? A literature review. Int J Equity Health; 5:3. doi:10.1186/1475-9276-5-3.
Jacobbi, V. (2023). 'Deaths of despair' contribute to 17% rise in Minnesota's death rate during COVID-19 pandemic. https://medicalxpress.com/news/2023-03-deaths-despair-contribute-minnesota-death.html
Jiang, D., Hou, Y., Hao, J., Zhou, J., Jiang, J., & Wang, Q. (2020). Association between personal social capital and loneliness among widowed older people. Int J Environ Res Public Health;17(16):5799.
Jose, P., Nicholas, R., & Pryor, J. (2012). Does social connectedness promote a greater sense of well‐being in adolescence over time? J Res Adolesc; 22:235-51doi:10.1111/j.1532-7795.2012.00783.x.
Kafetsios, K., & Sideridis. G. (2006). Attachment, social support and well-being in young and older adults. J Health Psychol.;11:863–75.
Kelley-Quon, L.I., Cho, J, Strong, D.R., Miech, R.A., Barrington-Trimis, J.L., et al. (2019). Association of nonmedical prescription opioid use with subsequent heroin use initiation in adolescents. JAMA Pediatr. 173(9):e191750
Kennedy, B.P., Kawachi, I., & Brainerd, E. (1998). The role of social capital in the Russian mortality crisis. World Dev. 26(11):2029–43
Kennedy, J., & King, L. (2014). The political economy of farmers’ suicides in India: indebted cash-crop farmers with marginal landholdings explain state-level variation in suicide rates. Glob. Health 10(1):16
King, L., Hamm, P., & Stuckler, D. (2009). Rapid large-scale privatization and death rates in ex-communist countries: an analysis of stress-related and health system mechanisms. Int. J. Health Serv. 39(3):461–89
King, L., Scheiring, G., & Nosrati, E. (2022). Deaths of despair in comparative perspective. Annual Review of Sociology, 48, 299-317.
King, C.A, Grupp-Phelan, J., Brent, D., et al., (2019). Pediatric Emergency Care Applied Research Network. Predicting 3-month risk for adolescent suicide attempts among pediatric emergency department patients. J Child Psychol Psychiatry; 60:1055-64. doi:10.1111/jcpp.13087 pmid:31328282
Kochanek, K.D., Murphy, S., Xu, J., Arias, E. (2017). Mortality in the United States, 2016. NCHS Data Brief.;(293):1-8.
Kuramoto-Crawford, S.J., Ali, M. M., & Wilcox, H.C. (2017). Parent-child connectedness and long-term risk for suicidal ideation in a nationally representative sample of US adolescents. Crisis; 38:309-18. doi:10.1027/0227-5910/a000439. pmid:27869507
Lancet (2023). Loneliness as a health issue. https://doi.org/10.1016/S0140-6736(23)01411-3
Landberg, J. (2008). Alcohol and suicide in Eastern Europe. Drug Alcohol Rev. 27(4):361–73
Lara, E., Martín-María, N., De la Torre-Luque, A., et al. (2019). Does loneliness contribute to mild cognitive impairment and dementia? A systematic review and meta-analysis of longitudinal studies. Ageing Res Rev; 52:7-16. doi:10.1016/j.arr.2019.03.002. pmid:30914351
Lawrence, W. R., Freedman, N. D., McGee-Avila, J. K., Berrington de González, A., Chen, Y., Emerson, M. A., Gee, G. C., Haozous, E. A., Haque, A. T., Inoue-Choi, M., Jackson, S. S., Lord, B., Nápoles, A. M., Pérez-Stable, E. J., Vo, J. B., Williams, F., & Shiels, M. S. (2023). Trends in Mortality From Poisonings, Firearms, and All Other Injuries by Intent in the US, 1999-2020. JAMA internal medicine, 183(8), 849–856. https://doi.org/10.1001/jamainternmed.2023.2509
Lim, K.K., & Chan, A. (2017). Association of loneliness and healthcare utilization among older adults in Singapore. Geriatr Gerontol Int.;17(11):1789–98.
Luanaigh, C.Ó., & Lawlor, B. A. (2008). Loneliness and the health of older people. Int J Geriatr Psych.;23:1213–21.
Luhmann, M., & Hawkley, L. C. (2016). Age differences in loneliness from late adolescence to oldest old age. Dev Psychol.;52(6):943–59.
Luo, Y., Hawkley, L.C., Waite, L.J, & Cacioppo, J.T. (2012). Loneliness, health, and mortality in old age: a national longitudinal study. Soc Sci Med.;74(6):907–14.
Mansfield, L., Daykin, N., & Meads, C., Tomlinson, A.l., &Gray, K., Lane, J. & Victor, C. (2019). A conceptual review of loneliness across the adult life course (16+ years).
Mansfield, L., Victor, C., Meads, C., Daykin, N., Tomlinson, A., Lane, J., Gray, K., Golding, A. (2021). A Conceptual Review of Loneliness in Adults: Qualitative Evidence Synthesis. International Journal of Environmental Research and Public Health; 18(21):11522. https://doi.org/10.3390/ijerph182111522
Marchant, A., Hawton, K., Stewart, A., et al. (2017). A systematic review of the relationship between internet use, self-harm and suicidal behaviour in young people: The good, the bad and the unknown. PLoS One;12:e0181722. doi:10.1371/journal.pone.0181722 pmid:28813437
Mijuskovic, B. (1981). Loneliness and human nature. Psychological Perspectives, 12(1): 69-77.
Murphy, S.L., Xu, J., Kochanek, K.D., Arias, E. (2018). Mortality in the United States, 2017. NCHS Data Brief.;(328):1-8.
Niedzwiedz, C.L., Richardson, E.A., Tunstall, H., Shortt, N.K., Mitchell, R.J., & Pearce, J.R. (2016). The relationship between wealth and loneliness among older people across Europe: is social participation protective? Prev Med.;91:24–31.Return to ref 14 in article
Nummela, O., Sulander, T., Karisto, A., & Uutela, A. (2009). Self-rated health and social capital among aging people across the urban-rural dimension. Int J Behav Med. 16:189–94. doi: 10.1007/s12529-008-9027-z,
Nyqvist, F., Victor, C.R., Forsman, A.K. et al. (2016). The association between social capital and loneliness in different age groups: a population-based study in Western Finland. BMC Public Health 16, 542. https://doi.org/10.1186/s12889-016-3248-x
Nyqvist, F., Nygård, M., & Scharf, T. (2021). Social Capital and Loneliness in Welfare State Regimes Before and After the Global Financial Crisis: Results Based on the European Social Survey. In: Almakaeva, A., Moreno, A., Wilkes, R. (eds) Social Capital and Subjective Well-Being. Societies and Political Orders in Transition. Springer, Cham. https://doi.org/10.1007/978-3-030-75813-4_12
Oldfield, J., Humphrey, N., & Hebron, J. (2016). The role of parental and peer attachment relationships and school connectedness in predicting adolescent mental health outcomes. Child Adolesc Ment Health; 21:21-9. doi:10.1111/camh.12108. pmid:32680365
Parkinson, J., Minton, J., Lewsey, J. et al. (2018). Drug-related deaths in Scotland 1979–2013: evidence of a vulnerable cohort of young men living in deprived areas. BMC Public Health 18, 357 https://doi.org/10.1186/s12889-018-5267-2
Parsons, M.A., & Barger, S.D. (2019). The US Mortality Crisis: An Examination of Non-Hispanic White Mortality and Morbidity in Yavapai County, Arizona. J Community Health 44, 661–667. https://doi.org/10.1007/s10900-019-00648-3
Perlman, D., & Peplau, L. (1982). Theoretical approaches to loneliness. In: Peplau LA, Perlman D, editors. Loneliness: A sourcebook of current theory, research and therapy. New York: John Wiley & Sons; p. 123–34.
Petrosino, A., Turpin-Petrosino, C., Hollis-Peel, M.E., & Lavenberg, J.G. (2013). ‘Scared Straight’ and other juvenile awareness programs for preventing juvenile delinquency. Cochrane Database Syst Rev;(4):CD002796. doi:10.1002/14651858.CD002796.pub2. pmid:23862186
Pinquart, M., & Sörensen, S. (2003). Risk factors for loneliness in adulthood and old age-a meta-analysis. In: Shohov SP, editor. Advances in psychology research. New York: Nova;. p. 111–43.
Putnam, R. D. (1994). Making democracy work: Civic traditions in modern Italy. New Jersey: Princeton University Press.
Putnam, R. D. (2000). Bowling alone: the collapse and revival of American community. New York: Simon & Schuster.
Putnam, R. (2018). Social capital: measurement and consequences. Harvard University, 2018. https://www.alnap.org/system/files/content/resource/files/main/1825848.pdf
Razvodovsky, Y. E. (2013). Psychosocial distress as a risk factor of ischemic heart disease mortality. Psychiatr. Danub. 25(1):68–75
Robinson, W.L., Whipple, C.R., Keenan, K., Flack, C.E., Wingate, L. (2022). Suicide in African American Adolescents: Understanding Risk by Studying Resilience. Annu Rev Clin Psychol.18:359-85. doi:10.1146/annurev-clinpsy-072220-021819 pmid:34762495
Rose, R. (2000). How much does social capital add to individual health? A survey of Russians. Soc. Sci. Med. 51:1421–35
Rotenberg, K. (1999). Childhood and adolescent loneliness: An introduction. In Loneliness in Childhood and Adolescence; Rotenberg, K., Hymel, S., Eds.; Cambridge University Press: Cambridge, UK; pp. 3–10. ISBN 9780511551888.
Rotenberg, K.J., Addis, N., Betts, L.R., Corrigan, A., Fox, C., Hobson, Z., Rennison, S., Trueman, M., & Boulton, M.J. (2010). The relation between trust beliefs and loneliness during early childhood, middle childhood, and adulthood. Pers Soc Psychol Bull.;36(8):1086–100.
Sadler, K., Vizard, T., Ford, T., Goodman, A., Goodman, R., & McManus, S. (2018). The mental health of children and young people in England 2017: trends and characteristics. Health and Social Care Information Centre. https://digital.nhs.uk/data-and-information/publications/statistical/mental-health-of-children-and-young-people-in-england/2017/2017
Sasakii N., Tabuch,i T., & Okubo, R., et al (2023). Association of living condition using urbanisation level and neighbourhood deprivation with loneliness and social isolation during COVID-19 pandemic: a cross-sectional study of the nationwide data in JapanBMJ Public Health;1:e000341. doi: 10.1136/bmjph-2023-000341
Sellers, R., Warne, N., Pickles, A., Maughan, B., Thapar, A., & Collishaw. S. (2019). Cross-cohort change in adolescent outcomes for children with mental health problems. J Child Psychol Psychiatry; 60:813-21. doi:10.1111/jcpp.13029 pmid:30989670
Shanahan, L., & Copeland, W. E. (2021). Psychiatry and Deaths of Despair. JAMA Psychiatry;78(7):695–696. doi:10.1001/jamapsychiatry.2021.0256
Shiels, M.S., Chernyavskiy, P., Anderson, W.F., et al. (2017). Trends in premature mortality in the USA by sex, race, and ethnicity from 1999 to 2014: an analysis of death certificate data. Lancet;389(10073):1043-1054. doi: 10.1016/S0140-6736(17)30187-3
Shiels, M. S., Berrington de González, A., Best, A. F., Chen, Y., Chernyavskiy, P., Hartge, P., Khan, S. Q., Pérez-Stable, E. J., Rodriquez, E. J., Spillane, S., Thomas, D. A., Withrow, D., & Freedman, N. D. (2019). Premature mortality from all causes and drug poisonings in the USA according to socioeconomic status and rurality: an analysis of death certificate data by county from 2000-15. The Lancet. Public health, 4(2), e97–e106. https://doi.org/10.1016/S2468-2667(18)30208-1
Shiels, M. S., Tatalovich, Z., Chen, Y., Haozous, E. A., Hartge, P., Nápoles, A. M., Pérez-Stable, E. J., Rodriquez, E. J., Spillane, S., Thomas, D. A., Withrow, D. R., Berrington de González, A., & Freedman, N. D. (2020). Trends in Mortality From Drug Poisonings, Suicide, and Alcohol-Induced Deaths in the United States From 2000 to 2017. JAMA network open, 3(9), e2016217. https://doi.org/10.1001/jamanetworkopen.2020.16217
Schuller, T., Baron, S., & Filed, J. (2000). Social capital: A review and critique. In: Baron S, Filed J, Schuller T, editors. Social capital: Critical perspectives. Oxford: Oxford University Press; p. 1–38.
Skrabski, Á., Kopp, M., & Kawachi, I. (2003). Social capital in a changing society: cross sectional associations with middle aged female and male mortality rates. J. Epidemiol. Commun. Health 57(2):114–19
Spillane, S., Shiels, M. S., Best, A. F., Haozous, E. A., Withrow, D. R., Chen, Y., Berrington de González, A., & Freedman, N. D. (2020). Trends in Alcohol-Induced Deaths in the United States, 2000-2016. JAMA network open, 3(2), e1921451. https://doi.org/10.1001/jamanetworkopen.2019.21451
Steelesmith, D. L., Lindstrom, M. R., Le, H. T., Root, E. D., Campo, J. V., & Fontanella, C. A. (2023). Spatiotemporal Patterns of Deaths of Despair Across the US, 2000–2019. American journal of preventive medicine.
Stein, E.M., Gennuso, K.P., Ugboaja, D.C., &Remington, P. L. (2017). The epidemic of despair among White Americans: trends in the leading causes of premature death, 1999-2015. Am J Public Health.;107(10):1541-1547. doi: 10.2105/AJPH.2017.303941
Sterling, P., & Platt, M. L. (2022). Why Deaths of Despair Are Increasing in the US and Not Other Industrial Nations—Insights From Neuroscience and Anthropology. JAMA Psychiatry;79(4):368–374. doi:10.1001/jamapsychiatry.2021.4209
Stumbrys, D., Jasilionis, D. & Pūras, D. (2022). The burden of mental health-related mortality in the Baltic States in 2007-2018. BMC Public Health 22, 1776. https://doi.org/10.1186/s12889-022-14175-9
Surkalim, D.L., Luo, M., Eres, R., et al. (2022). The prevalence of loneliness across 113 countries: systematic review and meta-analysis. BMJ;376:e067068. doi:10.1136/bmj-2021-067068. pmid:35140066
Tadaka, E., Kono, A., Ito, E., et al. (2016). Development of a community’s self-efficacy scale for preventing social isolation among community-dwelling older people (Mimamori Scale). BMC Public Health; 16:1198. doi:10.1186/s12889-016-3857-4 pmid:27894279
Tian, F., Li, H., Tian, S., Yang, J. Shao, J., Tian, C. (2020). Psychological symptoms of ordinary Chinese citizens based on SCL-90 during the level I emergency response to COVID-19. Psychiatry Res, 288: 112992.
Tomaka, J., Thompson, S., & Palacios, R. (2006). The relation of social isolation, loneliness, and social support to disease outcomes among the elderly. J Aging Health;18:359–84.
Tomioka, K., Kurumatani, N., & Hosoi, H. (2017). Age and gender differences in the association between social participation and instrumental activities of daily living among community-dwelling elderly. BMC Geriatr;17(1):99.
Twenge, J.M., Haidt, J., Blake, A.B., McAllister, C., Lemon, H., & Le Roy, A. (2021). Worldwide increases in adolescent loneliness. J Adolesc; 93:257-69. doi:10.1016/j.adolescence.2021.06.006 pmid:34294429
Ungar, M. (2004). The importance of parents and other caregivers to the resilience of high-risk adolescents. Fam Process; 43:23-41. doi:10.1111/j.1545-5300.2004.04301004.x pmid:15359713
Valtorta, N. K., Kanaan, M., Gilbody, S., Ronzi, S., & Hanratty, B. (2016). Loneliness and social isolation as risk factors for coronary heart disease and stroke: systematic review and meta-analysis of longitudinal observational studies. Heart;102(13):1009–16.
Vowles, K.E., McEntee, M.L., Julnes, P.S., Frohe, T., Ney, J.P., & van der Goes, D.N. (2015). Rates of opioid misuse, abuse, and addiction in chronic pain: a systematic review and data synthesis. Pain 156(4):569–76
Waldinger, R. & Schulz, M. (2023). The Good Life: Lessons from the World’s Longest Scientific Study of Happiness. Simon and Schuster. ISBN 9781982166694
Wills, T., & Yaeger, A. (2003). Family factors and adolescent substance use: models and mechanisms. Curr Dir Psychol Sci; 12:222-6doi:10.1046/j.0963-7214.2003.01266.x.
Woolcock, M. & Narayan, D. (2000). Social Capital. Implications for Development Theory, Research, and Policy. https://doi.org/10.1093/wbro/15.2.225
Woolf, S.H., Chapman, D.A., Buchanich, J.M., Bobby, K.J., Zimmerman, E.B., & Blackburn, S.M. (2018). Changes in midlife death rates across racial and ethnic groups in the United States: systematic analysis of vital statistics. BMJ. ;362: k3096. doi: 10.1136/bmj.k3096
Xu, J., Murphy, S.L, Kochanek, K. D., Arias, E. (2016). Mortality in the United States, 2015. NCHS Data Brief.;(267):1-8.
Yang, K., & Victor, C. R. (2011). Age and loneliness in 25 European nations. Ageing Soc.;31:1368–88
Yau, J.C., & Reich, S. M. (2018). Are the qualities of adolescents’ offline friendships present in digital interactions? Adolesc Res Rev;3: 339-55doi:10.1007/s40894-017-0059-y
Youngblade, L.M., Theokas, C., Schulenberg, J., Curry, L., Huang, I.C., & Novak, M. (2007). Risk and promotive factors in families, schools, and communities: a contextual model of positive youth development in adolescence. Pediatrics;119(Suppl1): S47-53. doi:10.1542/peds.2006-2089H pmid:17272585
Zhou, Z., Mao, F., Zhang, W., Towne, D.S., Wang, P., & Fang, Y. (2019). The association between loneliness and cognitive impairment among older men and women in China: a Nationwide longitudinal study. Int J Environ Res Public Health;16(16):2887.
Zhou, S.J., Zhang, L.G., Wang, L.L., Guo, Z.C., Wang, J.Q., Chen, J.C., et al. (2020). Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19. Eur Child Adolesc Psychiatry, 29: 749–758.
Zhu, C., Zhang, T., Li, Q. et al. (2023). Depression and Anxiety During the COVID-19 Pandemic: Epidemiology, Mechanism, and Treatment. Neurosci. Bull. 39, 675–684. https://doi.org/10.1007/s12264-022-00970-2

The authors declare no competing interests.

Download PDF

Version 1

posted

You are reading this latest preprint version

Social Capital: A Remedy for Deaths of Despair in the Rust Belt US Counties?

Status:

Version 1

Abstract

Figures

1 Introduction

2 Deaths of Despair (DoD)

3 Loneliness

4 Literature Review

5 Social Capital

6 Methodology

7 Econometric Analysis And Study Findings

8 Conclusion

References

Additional Declarations

Status:

Version 1