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Yemelyan Rodionov
Yemelyan Rodionov

7 Levels Of Wealth Manifestation Pdf ((INSTALL))



Think about it. The Bible does not say God makes you wealthy; it says He will give you the power to produce wealth (Deuteronomy 8:18). That means, He will always give you something to put your hands to, anoint your ability, and bring THE BLESSING on the scene when you are obedient to His commands.




7 Levels Of Wealth Manifestation Pdf



It also contains the programming you get from your family, culture and so on. If there were certain viewpoints about wealthy people, poverty, money being the root of all evil, something to be held on to tightly, something that comes naturally and easily and so on. This energy will be imprinted on you to some degree, regardless of whether not it was explicitly stated.


As you can see from just these three, there is going to be a very dynamic relationship going on between these 7 levels. In order to have a fully integrated and functional life around money that is able to receive, enjoy, save, create and much more in a wise way, you will want to work with each of these levels.


The 7 levels of wealth manifestation includes teaching around each level that creates a very comprehensive but logical, relatable model. This will give you a lot of clarity and insight into the big picture, and a lot of aha moments about how this all connects to money in a practical way.


More importantly, you do deep and intensive processing for each of the 7 levels. First there is often an exploration of the common wounds, vows and conflicts that reside in each one. You then process using EFT, which Margaret Lynch guides you through based on the core content of each level plus the responses and reactions from live callers.


Margaret is very good at leading the tapping rounds, an obviously experienced facilitator. She also really, really knows her stuff regarding the 7 levels/chakras, apparent from interactions with the live callers and how quickly she is able to relate their issue and put it in context.


Perceptions are confirmed by the persistence of disparities along the lines of socioeconomic position, gender, race, ethnicity, immigration status, geography, and the like has been well documented. Why? For one, historical inequities continue to ramify into the present. To understand how historical patterns continue to affect life chances for certain groups, historians and economists have attempted to calculate the amount of wealth transmitted from one generation to the next (Margo, 1990). They find that the baseline inequities contribute to intergenerational transfers of disadvantage and advantage for African Americans and whites, respectively (Chetty et al., 2014; Darity et al., 2001). The inequities also reproduce the conditions in which disparities develop (Rodriguez et al., 2015).


Discrimination is generally associated with worse mental health (Berger and Sarnyai, 2015; Gee et al., 2009; Paradies, 2006b; Williams and Mohammed, 2009); greater engagement in risky behaviors (Gee et al., 2009; Paradies, 2006b; Williams and Mohammed, 2009); decreased neurological responses (Harrell et al., 2003; Mays et al., 2007) and other biomarkers signaling the dysregulation of allostatic load; hypertension-related outcomes (Sims et al., 2012), though some evidence suggests racism does not drive these outcomes (Roberts et al., 2008); reduced likelihood of some health protecting behaviors (Pascoe and Smart Richman, 2009); and poorer birth-related outcomes such as preterm delivery (Alhusen et al., 2016). Paradoxically, despite higher levels of exposure to discrimination, the mental health consequences may be less severe among African Americans than they are among members of other groups, especially Asian populations (Gee et al., 2009; Williams and Mohammed, 2009). Researchers have suggested that African Americans draw on reserves of resilience in ways that temper the effects of discrimination on mental health (Brown and Tylka, 2011).


For the purposes of this report, the committee has identified nine social determinants of health (see report conceptual model, Figure 3-3) that the literature shows fundamentally influence health outcomes at the community level. These determinants are education, income and wealth, employment, health systems and services, housing, the physical environment, transporation, the social environment, and public safety (Table 3-1 provides a brief definition of each).


There is a vast and growing body of literature on the social, economic, and environmental determinants of health and their impacts on health outcomes (Braveman and Gottlieb, 2014; Braveman et al., 2011; CSDH, 2008; Marmot et al., 2010). Often, the evidence is in the form of cross-sectional analyses, and the pathways to health outcomes are not always clearly delineated, in part due to the complexity of the mechanisms and the long time periods it takes to observe outcomes (Braveman and Gottlieb, 2014). Therefore, the literature is not sufficient to establish a causal relationship between each of these determinants and health, but the determinants certainly are correlated with and contribute to health outcomes. While this report focuses on the community level, it should be made clear that the social determinants of health operate at multiple levels throughout the life course (IOM, 2006). This includes the individual level (knowledge, attitudes/beliefs, skills), family and community level (friends and social networks), institutional level (relationships among organizations), and systemic level (national, state, and local policies, laws, and regulations) (see Figure 3-2, the social ecological model adapted from McLeroy et al. [1988]). Furthermore, the various levels of influence that the social determinants of health have can occur simultaneously and interact with one another (IOM, 2006). In addition to the multiple levels of influence, there is a diversity of actors, sectors, settings, and stakeholders that interact with and shape the social determinants of health. This adds an additional layer of complexity to the factors that shape health disparities.


Education, as it pertains to health, can be conceptualized as a process and as an outcome. The process of educational attainment takes place in many settings and levels (e.g., the home/family, school, and community), while the outcome can be described as a sum of knowledge, skills, and capacities that can influence the other social determinants of health, or health, more directly (Davis et al., 2016). Within the current social determinants of health literature, the primary focus on education is on educational attainment as an outcome (i.e., years of schooling, high school completion, and number of degrees obtained) and how it relates to health outcomes.


The evidence suggests that disparities in education are apparent early in the life course, which reflects broader societal inequities (Garcia, 2015). In education, these early disparities are evidenced by wide gaps in vocabulary between children from low-income and those from middle- or upper-income families. Children from low-income families may have 600 fewer words in their vocabulary by age 3, a gap that grows to as many as 4,000 words by age 7 (Christ and Wang, 2010). These word gaps directly affect literacy levels and reading achievement (Marulis and Neuman, 2010). There is substantial evidence that children who do not read at grade level by 7 or 8 years of age are much more likely to struggle academically (Chall et al., 1990). Both high school graduation rates and participation in postsecondary education opportunities are correlated with early literacy levels. Hence, attention to and investments in early childhood education are generally viewed as an important way to reduce disparities in education (Barnett, 2013).


Access to financial resources, be it income or wealth, affects health by buffering individuals against the financial threat of large medical bills while also facilitating access to health-promoting resources such as access to healthy neighborhoods, homes, land uses, and parks (Davis et al., 2016). Income can predict a number of health outcomes and indicators, such as life expectancy, infant mortality, asthma, heart conditions, obesity, and many others (Woolf et al., 2015).


Not only are income and wealth determinants of health, but the concentration of poverty in certain neighborhoods is important to recognize as a factor that shapes the conditions in which people live. Concentrated poverty, measured by the proportion of people in a given geographic area living in poverty, can be used to describe areas (e.g., census tracts) where a high proportion of residents are poor (Shapiro et al., 2015). Concentrated poverty disproportionately affects racial and ethnic minorities across all of the social determinants of health. For example, National Equity Atlas data reveal that in about half of the largest 100 cities in the United States, most African American and Hispanic students attend schools where at least 75 percent of all students qualify as poor or low-income under federal guidelines (Boschma, 2016). Given that concentrated poverty is tightly correlated with gaps in educational achievement, this has implications for educational outcomes and health (Boschma and Brownstein, 2016).


In 2012, of the 12 million full-time low-income workers between the ages of 25 and 64, 56 percent were racial and ethnic minorities (Ross, 2016b). Regional percentages varied from 23 percent in Honolulu, Hawaii, to 65 percent in Brownsville, Texas (Ross, 2016a). Figure 3-7 shows the proportion of low-income workers of racial and ethnic minority groups across different regions of the United States. The burden faced by low-income people suggests that efforts to advance health equity through income and wealth will need to take into consideration rising income inequality as well as significant geographic variation.


Chronic diseases are more prevalent among low-income people than among the overall U.S. population. Low-income adults have higher rates of heart disease, diabetes, stroke, and other diseases and conditions relative to adults earning higher levels of income (Woolf et al., 2015).


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