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By F. Zapotek. Norfolk State University. 2018.

Maintaining contact with their families is extremely difficult buy stromectol 3 mg on-line infection z movie; family stability and well- being are jeopardized when a breadwinner or parent is taken away cheap stromectol 3mg with amex bacteria die when they are refrigerated or frozen. The consequences of a criminal conviction last far longer than the time spent in jail or prison. People with criminal records experience what can be a lifetime of stigma and legal discrimination in employment, housing, education, public benefits, jury service, and the right to vote. Families and communities are injured by these policies as well (Mauer and Chesney-Lind 2003; Western 2006; Clear 2007). A number of conclusions leap from readily available data: • Black Americans are much more likely than white Americans to be arrested and incarcerated for drug crimes. In short, racial disparities in arrest and imprisonment for drug crimes cannot be explained by racial patterns of drug crime. There are operational reasons for the disparities; most importantly, drug law enforcement activities are concentrated in inner city areas with high minority populations. But law enforcement’s strategic choices in turn reflect the longstanding influence of race on how the United States has defined the drug problem. Section I of this article discusses and documents the role of race in the development of drug control efforts in the United States and presents statistics revealing that black Americans have been and continue to be arrested, convicted, and incarcerated on drug charges at rates far higher than those for whites. Blacks are arrested on drug charges at three times the rate for whites and are sent to state prison1 on drug charges at 10 times the rate for whites. The net result is that more black than white Americans are doing time for drug offenses in a country in which only 12. The arrest and incarceration disparities cannot be explained by racial differences in drug offending because there are far more white than black drug offenders. Overall, slightly larger percentages of black people have used illegal drugs in the past year or month, although a higher percentage of white people have used drugs in their lifetime. In absolute numbers, however, the numbers of white users of illicit drugs—even crack—dwarf black numbers because there are five to six times as many white as black Americans. Evidence of racial patterns in drug trafficking is less strong than concerning use, but what there is suggests that black drug-selling rates are little or no higher than white rates and, accordingly, that there are many more white than black sellers. Arrest rates are much higher for blacks than whites largely because police focus drug law enforcement on places, principally inner-cities, with high minority populations and target their resources where drug arrests are easiest —on the streets, rather than in private home or office buildings. Imprisonment disparities are even worse than arrest disparities with blacks more likely to be sentenced to prison for drug offenses and to receive longer sentences than whites. To some extent, longer sentences for black drug offenders reflect federal and some state drug laws that mandate especially severe penalties for crack offenses for which blacks are disproportionately arrested. They also reflect the fact that black drug arrestees are more likely to have prior convictions that lead to sentence enhancements. Racial disparities in drug law enforcement result from the combined effects of many social, geographic, and political factors operating at federal, state, and local levels, but they also reflect the influence of racialized considerations and concerns in the decisions of legislators, police, prosecutors, and judges. Overt racial prejudice may not be at work, but extensive research and analysis over the past few decades leave little doubt that antidrug efforts are rooted in and reflect the unconscious racial bias of whites against blacks as well as race relation dynamics that benefit whites to the detriment of blacks. The United States has a human rights obligation to end such disparities, but it cannot do so until it acknowledges how deeply racial discrimination has permeated its antidrug efforts. Race and Drug Laws Crimes are social constructs, reflecting historically evolving and culturally specific sets of moral views and social and political imperatives. The wrongfulness of certain behavior, for example, murder, is intuitively understood by most people to warrant criminalization. Whether and why the possession and sale of certain substances used for recreation should be criminalized is far less easy to understand (Husak 1992, 2008). It is also a story about race and ethnicity: group antagonisms, fears, and tensions have played powerful roles in shaping U. Criminalization of drugs was historically one way that dominant, white social groups sought to maintain control over racial and ethnic minorities who troubled, angered, or scared them (Musto 1999). Advocates of criminalization have consistently painted drug users as morally weak (if not depraved), dangerous, and a threat to community standards and upstanding people. Advocates of criminalization have also tended to be most concerned about drugs associated with racial and ethnic groups that, in various ways, they thought threatened white America. Overt and virulent racism was2 pervasive in alcohol and drug control debates from the 1870s through the 1960s, giving social and political heft to public health messages and the efforts of prohibitionist “moral entrepreneurs. Although overt racism disappeared from drug policy debates after the civil rights movement took hold, racial concerns nonetheless helped propel the modern “war on drugs” launched during the Reagan administration (Reinarman and Levine 1997; Tonry 1995, 2011). The use of cocaine, primarily powder cocaine, increased in the late 1970s and early 1980s, particularly among whites, but did not provoke the “orgy of media and political attention” that occurred in the mid-1980s when a cheaper, smokable form of cocaine, in the form of crack, appeared.

They are well suited for studying rare diseases since the study begins with subjects who already have the outcome cheap 3mg stromectol mastercard virus definition biology. Each case patient may then be matched up with one or more suitable control patients generic stromectol 3mg fast delivery antibiotics for mild acne. Ideally the controls are as similar to the cases as pos- sible except for the outcome and then their degree of exposure to the risk fac- tor of interest can be calculated. Case–controls are good exploratory studies and can look at many risk factors for one outcome. Unfortunately, there are many potentially serious weaknesses in case–control studies, which in general, make them only fair sources of evidence. Data often come from a careful search of the medical records of the cases and controls. The advantage of these records being easily available is counteracted by their questionable reli- ability. These studies rely on subjective descriptions to determine exposure and outcome, and the subjective standards of the record reviewers to determine the presence of the cause and effect. Implicit review of charts introduces the researcher’s bias in interpreting the measurements or outcomes. An explicit review only uses clearly objective measures in reviews of medical charts, or the chart material is reviewed in a blinded manner using pre- viously determined outcome descriptors. When a patient is asked to remember something about a medical condi- tion that occurred in the past, their memory is subject to recall or reporting bias. Recall or reporting bias occurs because those with the disease are more likely to recall exposure to many risk factors simply because they have the dis- ease. Another problem is that subjects in the sample may not be representative of all patients with the outcome. This is called sampling or referral bias and 62 Essential Evidence-Based Medicine commonly occurs in studies done at specialized referral centers. These referred patients may be different from those seen in a primary-care practice and often in referral centers, only the most severe cases of a given disorder will be seen, thus limiting the generalizability of the findings. When determining which of many potential risk factors is associated with an outcome using a case–control study a derivation set is developed. The results of the derivation set should be used cautiously since any association discovered may have turned up by chance alone. The study can then be repeated using a cohort study design to look at those factors that have the highest correlation with the outcome in ques- tion to see if the association still holds. This is called a validation set and has greater generalizability to the population. Other factors to be aware of when dealing with case–control studies are that case–controls can only study one disease or outcome at a given time. Also, preva- lence or incidence cannot be calculated since the ratio of cases to controls is pre- selected by the researchers. In addition, they cannot prove contributory cause since they cannot show that altering the cause will alter the effect and the study itself cannot show that the cause preceded the effect. Often times, researchers and clinicians can extrapolate the cause and effect from knowledge of biology or physiology. Cohort studies These were previously called prospective studies since they are usually done from past to present in time. The name comes from the Latin cohors, meaning a tenth of a legion marching together in time. However, they can be and are now as frequently done retrospectively and called non-concurrent cohort studies. The cohort is a group of patients who are selected based on the presence or absence of the risk factor (Fig. They are followed in time to determine which of them will develop the outcome or disease. The probability of developing the outcome is the incidence or risk, and can be calculated for each group. They can be powerful studies that can determine the incidence of disease and are able to show that the cause is associated with the effect more often than by chance alone.

If there is only poor quality of evidence buy stromectol 3 mg amex antibiotic you cant drink on, such as would be available only from a case series generic stromectol 3 mg with mastercard antibiotic jab, the provider will be less confident in the quality of the evidence and should convey more uncertainty. Pitfalls to providing the evidence The most common pitfall when providing evidence is giving the patient more information than she wants or needs although often the most noteworthy pit- falls are related to the misleading nature of words and numbers. The answer given to the patient is: “Usually headaches like yours are caused by stress. Only in extremely rare circumstances is a headache like yours caused by a brain tumor. In this example, expressing the common nature of stress headaches as “usually” can be very vague. When res- idents and interns in medicine and surgery were asked to quantify this term, they chose a range of percents between 50–95%. In this example stating that headaches due to a brain tumor occurred only in “extremely rare” circum- stances is also imprecise. When asked to quantify “extremely rare” residents and interns chose a range of percents between 1–10%. Knowing that the disease is rare or extremely rare may be consoling, but if there is a 1 to 10% chance that it is present, this may not be very satisfactory for the patient. It is clear that there is a great potential for misunderstanding when converting numbers to words. Unfortunately, using actual numbers to provide evidence is not necessarily clearer than words. For example in a study where the outcomes are reported in binary terms such as life or death, or heart attack or no heart attack, a physician can describe the results numerically as a relative risk reduction, an absolute risk reduction, a number needed to treat to benefit, length of survival or disease-free interval. When describing outcomes, results have the potential to sound quite different Communicating evidence to patients 205 to a patient. The following example describes the same outcome in different ways: r Relative risk reduction: This medication reduces heart attacks by 34% when compared to placebo. This also means that for every 71 patients treated, 70 get no additional benefit from taking the medication. When treatment benefits are described in relative terms such as a relative risk reduction, patients are more likely to think that the treatment is helpful. The description of outcomes in absolute terms such as absolute risk reduction, leads patients to perceive less benefit from the medications. This occurs because the relative changes sound bigger than absolute changes and are, therefore, more attractive. A patient’s ability to understand study results for diagnostic tests may be ham- pered by using percentages instead of frequencies to describe those outcomes. Gigerenzer has demonstrated that for most people, describing results as 2% instead of 1 in 50 will more likely be confusing (see the Bibliography). Using these “natural frequencies” to describe statistical results can make it much easier to understand fairly complex statistics. When describing a diagnostic test using nat- ural frequencies, give the sensitivity and specificity as the number who have dis- ease and will be detected (True Positive Rate) and the number who don’t have the disease and will be detected as having it (False Positive Rate). Then you can give the numbers who have the disease and a positive or negative test as a propor- tion of those with a positive or negative test. The concept of natural frequencies has been described in much more detail by Gerd Gigerenzer in his book about describing risk. Patients’ interpretations of study results are frequently affected by how the results of the study are presented, or framed. For example, if a study evaluated an outcome such as life or death, this can be presented in either a positive way by saying that 4 out of 5 patients lived or a negative way, that 1 out of 5 patients died. The use of positive or negative terms to describe study outcomes does influence a patient’s decision and is described as framing bias. They were asked to imagine they had lung cancer and to choose between surgery and radiation therapy.

The amounts needed generic stromectol 3 mg line antibiotics for uti late period, however purchase 3 mg stromectol visa best antibiotic for sinus infection cephalexin, each constitute only a small percentage of total energy requirements. While some nutrients are present in both animal- and plant-derived foods, others are only present or are more abundant in either animal or plant foods. For example, animal-derived foods contain significant amounts of protein, saturated fatty acids, long-chain n-3 polyunsaturated fatty acids, and the micronutrients iron, zinc, and vitamin B12, while plant-derived foods provide greater amounts of carbohydrate, Dietary Fiber, linoleic and α-linolenic acids, and micronutrients such as vitamin C and the B vitamins. It may be difficult to achieve sufficient intakes of certain micronutrients when consuming foods that contain very low amounts of a particular macronutrient. Alternatively, if intake of certain macronutrients from nutrient-poor sources is too high, it may also be difficult to consume sufficient micronutrients and still remain in energy balance. Therefore, a diet containing a variety of foods is considered the best approach to ensure sufficient intakes of all nutrients. This concept is not new and has been part of nutrition education pro- grams since the early 1900s. Department of Agriculture in 1916 and suggested consumption of a combination of five different food groups (Guthrie and Derby, 1998). Similarly, Canada has developed Canada’s Food Guide to Healthy Eating (Health Canada, 1997). However, these studies demonstrate associa- tions; they do not necessarily infer causality, such as would be derived from controlled clinical trials. Robust clinical trials with specified clinical endpoints are generally lacking for macronutrients. It is not possible to determine a defined level of intake at which chronic disease may be prevented or may develop. For example, high fat diets may predispose to obesity, but at what percent of energy intake does this occur? The answer depends on whether energy intake exceeds energy expenditure or is balanced with physical activity. This chapter reviews the scientific evidence on the role of macro- nutrients in the development of chronic disease. In addition, the nutrient limitations that can occur with the consumption of too little or too much of a particular macronutrient are discussed. These ranges represent (1) intakes that are asso- ciated with reduced risk of chronic disease, (2) intakes at which essential dietary nutrients can be consumed at sufficient levels, and (3) intakes based on adequate energy intake and physical activity to maintain energy balance. Furthermore, chronic consumption of a low fat, high carbohydrate or high fat, low carbohydrate diet may result in the inadequate intake of certain essential nutrients. In this section, the rela- tionship between total fat and total carbohydrate intakes are considered. For example, a low fat diet signifies a lower percentage of fat relative to total energy. It does not imply that total energy intake is reduced because of consumption of a low amount of fat. The distinction between hypocaloric diets and isocaloric diets is important, particularly with respect to impact on body weight. The failure to identify this distinction has led to considerable confusion in terms of the role of dietary fat in chronic disease. Consequently, there are two issues to consider for the distribution of fat and carbohydrate intakes in high-risk populations: the distributions that predispose to the development of overweight and obesity, and the distributions that worsen the metabolic consequences in popula- tions that are already overweight or obese. Maintenance of Body Weight A first issue is whether a certain macronutrient distribution interferes with sufficient intake of total energy, that is, sufficient energy to maintain a healthy weight. Sonko and coworkers (1994) concluded that an intake of 15 percent fat was too low to maintain body weight in women, whereas an intake of 18 percent fat was shown to be adequate even with a high level of physical activity (Jéquier, 1999). Moreover, some populations, such as those in Asia, have habitual very low fat intakes (about 10 percent of total energy) and apparently maintain adequate health (Weisburger, 1988). Whether these low fat intakes and consequent low energy consumptions have con- tributed to a historically small stature in these populations is uncertain. An issue of more importance for well-nourished but sedentary popula- tions, such as that of the United States, is whether the distribution between intakes of total fat and total carbohydrate influences the risk for weight gain (i. It has been shown that when men and women were fed isocaloric diets containing 20, 40, or 60 percent fat, there was no difference in total daily energy expenditure (Hill et al. Similar observations were reported for individuals who consumed diets containing 10, 40, or 70 percent fat, where no change in body weight was observed (Leibel et al.