The Latter Is Derived From A Chart That Lists Three Categories Of Weight Ranges

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The opposition for a woman to reach an agreement in salary and in the position of a man was still too stiff,and not all party colleagues were willing to take the risk. Another significant example was made up by Ruth H. McCormick,who when opting for Congress by the state of Illinois in 1928,was quite surprised by the vehemence of the resistance of her candidacy for the mere fact of being a woman. In an anonymous letter she received from a voter,it was affirmed: “I would not think to vote for a woman to Congress more than one of my cows for that position of responsibility”.Neither her own friends were very determined to support her because they felt she had no chance of succeeding. A bit later,when she won the Republican nomination for the Senate,many politicians were alarmed by the idea of a woman in the Senate,despite the number of women who had served in the House of Representatives. Hiram Johnson,travelling companion of Teddy Roosevelt in 1912,made the following statement: “It is quite true that the Senate may not have been sensitive to the traditions of the past few years,but it is by breaking them which will lead to ...
... the admission of the other sex to the Senate”. Moreover,almost all the women elected stated that the men who worked with them were quite friendly and hospitable towards them. When historian Sophonisba Breckinridge investigated women state legislators,most of them said that their legislative experience was quite interesting and rewarding. However,at the same time,many still perceived that women were used as labor policy by male leaders and that they were given little positions with effective or real power. And certainly,there were many cases of discrimination in finding that they did not have sufficient political skills.Diabetes Mellitus is considered as an epidemic,which principally applies to type 2 diabetes mellitus the “natural history of which can be changed” by detection and management of prediabetes with life-style modifications and simple pharmacotherapy.Once established,especially with complications,DM has escalating health and financial burdens in the USA and globally. The prevalence of DM continues to rise steadily; in the USA,DM and its precursor,PreDM,together affect over 1/3 of the US population at present. More concerning is that about 90% of patients with PreDM and 30% of patients with DM,desktop whiteboard respectively,remain undiagnosed,and that at the time of DM diagnosis,one or more of the diabetes complications would have already occurred in many patients.

In the dental domain,periodontal disease is considered as one of the complications of uncontrolled DM,and a bi-directional relationship has been observed between uncontrolled DM and PD. Furthermore,PD has also been reportedly associated with PreDM,which underscores the notion that even mild degrees of hyperglycemia can cause diabetic complications,including PD. Ineffective screening was cited as a major contributing factor to the high prevalence of undiagnosed DM and PreDM. Hence there is the need for more effecting screening campaigns.Dental offices encounter a large sector of the population annually; Herman et al. reported that up to 70% of Americans saw dentists at least once a year. They also reported that a national survey of dental patients over the age 50 found a prevalence of 10% of DM and 40% of PreDM,and that up to 50% and over 90% of these patients,respectively,were undiagnosed. It was also reported that many dental patients may not see a family physician on a regular basis. By taking these data and observations together,it is thus conceivable that amongst the dental populations,there is potentially a significant prevalence of undiagnosed DM and PreDM,in parallel with national statistics. Furthermore,Greenberg et al. reported a satisfactory response by American dentists for screening for systemic diseases,with 76.6% favoring screening for DM. Recently,several studies have been published that proved the effectiveness of diabetes screening in the dental office. Therefore,dentists can benefit from a simple DM self-screening questionnaire that will help them identify patients at risk for PreDM and DM who should be appropriately referred for diagnostic testing by any of the established American Diabetes Association ’s criteria. Therefore this study was conducted to design a self-screening tool and compare it to a standardized laboratory diagnostic test to evaluate its predictive ability. The major objective of the study was to develop a dental-office-friendly screening tool that would potentially garner wide-spread acceptance by dentists: Simple,chair-side,self-screening questionnaire from which dentists could refer patients for diagnostic confirmation. This questionnaire requires no clinical assistance from the dental team: No numerical measurement of body weight,no discussion of body weight,no calculation of BMI and no additional medical screening tests such as blood pressure recording,or blood lipid panel. Another objective of the study is to design an online simple,dental- focused,diabetes self-screening tool for public use.Each participant completed the proposed PreDM/DM screening tool by answering 14 binary yes-or-no questions without assistance or discussion. In an attempt to include all relevant questions in the study questionnaire,we searched the literature for any/all published diabetes self-screening tools. Several screening tools have been developed thus far for the detection of undiagnosed DM and PreDM in non-dental settings,varying in methodology and ease of application.

Nevertheless,Bang et al. found limited evidence for use of these tools in clinical practice. In searching the literature for an existing screening tool for PreDM and DM which was developed specifically for use in dental offices,we only found one such screening tool that was published recently by Herman et al.,at the time of the completion of our study. However,we found that the questionnaire utilized by Herman et al. included actual calculation of body mass index,based on self-reported weight and height. This particular issue is undesirable in dental offices; in general,dental patients and providers are not comfortable with discussing exact weight or BMI during dental visits. Furthermore,in Herman’s multi-staged study,and while initially enrolling 1033 subjects,the authors reported that only 28% of participants returned for completion of subsequent study protocol. This diluted the number of the study subjects to only 181. We believe these are 2 significant limitations to the findings of this study. In the proposed survey,we included the self-reporting of established variables,as collected from previously published risk and screening tools,to be evaluated in a real life dental setting—a general dental office. We ultimately selected risk factors or symptoms that we incorporated into a 14-questions survey. As noted,the risk factors included questions about risk for T2DM,hyperglycemic symptoms and diabetic complications. The questions did not include exact measurements nor reporting of weight,BMI or waist circumference. Furthermore,we found that the majority of the published diabetes screening tools included either performing physical measurements such as blood pressure or drawing labs such as lipid profiles.Each participant underwent a finger-stick for collection of capillary blood for laboratory A1c measurement. The finger-stick and capillary collection was performed by two research personnel trained by Sparrow Hospital phlebotomists,using a single-use device. The device was designed for A1c testing. The capillary tube was then placed into the sample preparation vial which was then capped and shaken. These blinded vials were sent in batches at 4˚C to the Diabetes Diagnostic Laboratory at the University of Missouri,Columbia,Missouri. A1c was measured from these pre-diluted samples by the Tosoh G8 ion-exchange HPLC method in an NGSP Secondary Reference Laboratory. The method of capillary collection has previously been validated for the Tosoh G8 assay by comparison of paired samples from fresh whole blood and capillary collection vials. The results of the samples,A1c blood levels were reported back and correlated with the corresponding surveys for statistical analysis of each individual question.

In this study,we report the feasibility,acceptability and effectiveness of screening for DM and Pre DM in the dental office,confirming findings of previously published dental studies. Furthermore,we report the development a simplified,user-friendly self-screening survey for the detection of undiagnosed PreDM and DM,concealment shelf designed for ease of use in the dental office. We derived our screening variables from the 13 published diabetes screening tools/questionnaires. These screening tools represented the following populations:US;UK;Dutch;and 1 tool each from Finland,Denmark,Italy,Germany and Australia. We sought to develop a screening tool applicable to the US population,and hence we limited our in-depth review to US published screening tools. The first US screening tool was developed in 1995 by Herman et al. and was based on the National Health and Nutrition Survey population,cohort II. The questionnaire included age,weight above 20% of IBW,based on medium body frame,family history of diabetes,delivery of a baby > 9 lbs. and level of physical activity. The questions were given “Yes” or “No” option,and were stratified into 3 categories per age groups,20 - 44,45 - 64 and ≥ 65 years. In 2008,Heikes et al. developed a well-designed,but conceivably sophisticated new screening tool,also utilizing the NHANES population. The authors added more variables of known diabetic risk factors: Age; family history,hypertension,physical activity,and prior gestational diabetes. For weight,the authors used cut-offs for WC and Weight based on height above or below 63.1”. The model begins with stratification of patients into age above or below 44 years,and then if WC is above or below 38.4”. In 2012,Bang et al. developed the third US diabetes screening tool. The authors also utilized the NHANES population. This model was derived from multiple available screening tools including instruments developed by the Center for Disease Control,the American Diabetes Association and the US Preventive Services Task Force. The model was then validated on the NHANES,ARIC and the CHS cohorts. The weight variable was based on BMI. Most recently,and at the time of completion of our study,Herman et al. published a new study that is similar to ours. However,as reviewed earlier,Herman’s recent study suffered from lack of response of participants,thus diluting the ultimate study sample size to 181 participants. Furthermore,Herman et al. used BMI in the study,which is an issue that poses some inconvenience at the dental office,as alluded to earlier. Finally,Herman et al. did not derive an online/digital screening tool from their study. Based on the models of Herman,Heikes,and Bang,the ADA developed a diabetes questionnaire that allows individuals to estimate their diabetes risk,which is available online for public use at the ADA website.