Willis L. Owen

A comparison between BMI and Conicity index on predicting coronary heart disease: the Framingham Heart Study.

PURPOSE This study examined the relationship of mortality and morbidity of coronary heart disease with body mass index (BMI) and Conicity index (CI). METHODS Among 5209 Framingham Heart Study participants, 1882 men and 2373 women had waist and weight measurement at the 4th examination period and height measured on the 5th visit. These were used for BMI and CI. RESULTS During a 24-year follow-up, 597 men and 468 women developed CHD and 248 men and 150 women died from CHD associated causes. In men the relative risks (RR) (95% confidence interval) adjusted for age, hypertension, diabetes, smoking status, and total cholesterol for CHD incidence in 2nd, 3rd, and 4th quartiles of BMI were 1.28 (1.0, 1.65), 1.45 (1.13, 1.86), and 1.53 (1.19, 1.96). The RR for CHD incidence in the 4th quartile of BMI in women was 1.56 (1.16, 2.08). No CI quartiles were risk factors for CHD incidence. There was 86% higher risk of CHD related death in the 4th quartile of BMI than the 1st quartile of BMI in women. In men no significantly higher risks of death were found across the quartiles of BMI. No associations were found between CI quartiles and CHD mortality. CONCLUSIONS Obesity as measured by BMI is an important risk factor for CHD incidence in men and women and for CHD mortality in women. CI was not associated with an increase in CHD incidence or mortality. Thus, BMI is a better marker than CI for predicting CHD incidence and mortality.

Experimental and Quasi-Experimental Research

Research design is the plan, structure, and strategy of investigation conceived so as to obtain answers to research quest ions and to control variance. Research design has two basic purposes: (1) to provide answers to research questions and (2) to control variability. The main technical function of research design is to control variance: Maximize systematic variability, control extraneous systematic variability, and minimize error variability.

Antibody Response to Actinomyces Antigen and Dental Caries Experience: Implications for Caries Susceptibility

ABSTRACT Fluoridated dentifrices reduce dental caries in subjects who perform effective oral hygiene. Actinomyces naeslundii increases in teeth-adherent microbial biofilms (plaques) in these subjects, and a well-characterized serum immunoglobulin G (IgG) antibody response (Actinomyces antibody [A-Ab]) is also increased. Other studies suggest that a serum IgG antibody response to streptococcal d-alanyl poly(glycerophosphate) (S-Ab) may indicate caries experience associated strongly with gingival health and exposure to fluoridated water. The aim of this study was to investigate relationships between A-Ab response, oral hygiene, S-Ab response, and caries experience. Measurements were made of A-Ab and S-Ab concentrations, caries experience (number of decayed, missing, and filled teeth [DMFT], number of teeth surfaces [DMFS], and number of decayed teeth needing treated [DT]), exposure to fluoridated water (Flu), mean clinical pocket depth (PD; in millimeters), and extent of plaque (PL) and gingival bleeding on probing (BOP). A-Ab concentration, the dependent variable in a multiple regression analysis, increased with S-Ab concentration and decreased with PL and DMFT adjusted for Flu (R2 = 0.51, P < 0.002). Residual associations with age, DMFS, DT, and BOP were not significant. In addition, an elevated A-Ab response, defined from immunoprecipitation and immunoassay measurements, indicated a significant, 30% reduction in DMFT after adjustment for significant age and Flu covariance (analysis of variance with covariance F statistic = 10.6, P < 0.003; S-Ab response and interactions not significant). Thus, an elevated A-Ab response indicates less caries in subjects performing effective oral hygiene using fluoridated dentifrices. Conversely, a low A-Ab response is suggestive of decreased A. naeslundii binding to saliva-coated apatite and greater caries experience, as reported by others.

Introduction to nutrition and health research

Preface. Acknowledgements. Part I: Overview of the Research Process. 1. Introduction to Research in Nutrition and Health. 2. Research Problem and Literature Review. 3. Framing a Research Problem: Hypotheses, Purposes, Objectives, and Questions. 4. Writing Method Sections. 5. Ethical Issues in Research and Scholarship. Part II: Statistical and Measurement Concepts in Research. 6. Statistical Concepts. 7. Relationships Among Variables. 8. Differences Among Groups. 9. Nonparametric Statistics. 10. Measuring Research Variables. Part III: Various Types of Research. 11. Experimental and Quasi-Experimental Research. 12. Descriptive Research and Qualitative Research. Part IV: Writing the Research Proposal and Results. 13. Results, Discussion, and Abstract. 14. Publications. 15. Writing the Research Proposal. Part V: Using Computers in Research. 16. Using Computers. Appendix: A. Statistical Tables. Subject Index.

Measuring Research Variables

“In its broadest sense, measurement is the assignment of numerals to objects or events according to rules (Stevens).” This definition of measurement accurately expresses the basic nature of measurement. A numeral is a symbol of the form: 1,2.3, ..., or I, II, III .... etc. There are four general levels of measurement: nominal, ordinal, interval, and ratio that we have already discussed in Chapter 6.

Differences Among Groups

Statistical techniques are used for describing and finding relationships among variables, as we discussed in Chapters 6 and 7. They are also used to detect differences among groups. The latter are most frequently used for data analysis in experimental and quasi-experimental research. They enable us to evaluate the effects of an independent [cause or treatment or categorical variables (gender, age, race, etc.)] variable on a dependent variable (effect, outcome).

Elevated antibody to D-alanyl lipoteichoic acid indicates caries experience associated with fluoride and gingival health

BackgroundAcidogenic, acid-tolerant bacteria induce dental caries and require D-alanyl glycerol lipoteichoic acid (D-alanyl LTA) on their cell surface. Because fluoride inhibits acid-mediated enamel demineralization, an elevated antibody response to D-alanyl LTA may indicate subjects with more acidogenic bacteria and, therefore, an association of DMFT with fluoride exposure and gingival health not apparent in low responders.MethodsCluster analysis was used to identify low antibody content. Within low and high responders (control and test subjects), the number of teeth that were decayed missing and filled (DMFT), or decayed only (DT) were regressed against fluoride exposure in the water supply and from dentrifice use. The latter was determined from gingival health: prevalences of plaque (PL) and bleeding on probing (BOP), and mean pocket depth (PD). Age was measured as a possible confounding cofactor.ResultsIn 35 high responders, DMFT associated with length of exposure to fluoridated water (F score), PL and BOP (R2 = 0.51, p < 0.001), whereas in 67 low D-ala-IgG responders, DMFT associated with PL, age, and PD (R2 = 0.26, p < 0.001). BOP correlated strongly with number of 7 7 decayed teeth (DT) in 54 high responders (R2 = 0.57, p < 0.001), but poorly in 97 low responders (R2 = 0.12, p < 0.001). The strength of the PD association with DMFT, or of BOP with DT, in high responders significantly differed from that in low responders (p < 0.05).ConclusionCaries associates with gingival health and fluoridated water exposure in high D-alanyl LTA antibody responders.

Relationships Among Variables

In the previous chapter hypothesis testing was explained. Another area of inferential statistics involves determining whether a relationship between two or more variables exists. For example, nutritionists may want to know whether caffeine intake is related to heart disease, or whether person’s age is related to her blood pressure. A zoologist may want to know whether the birth weight of a certain animal is related to the life span of the animal. These are only a few of the many questions that can be answered by using the technique of correlation and regression analysis. Correlation is a statistical method used to determine whether a relationship between variables exists. Regression is a statistical method used to describe the nature of the relationship between variables — i.e., a positive or negative, linear or nonlinear relationship.

Incorporation of Simethicone into Syrupy or Clear Base Liquid Orals

AbstractThe objective of this project was to incorporate simethicone in a syrupy or clear base liquid oral.Best results were obtained when a commercially available emulsion concentrate was stabilized with Carbopol® resins. The use of 0.2% neutralized Carbopol® resin in combination with glycerin and propylene glycol produced a very stable formulation which did not show any separation or creaming for the duration of the studies.

Descriptive Research and Qualitative Research

Descriptive research is a study of status and is widely used in education, nutrition, epidemiology, and the behavioral sciences. Its value is based on the premise that problems can be solved and practices improved through observation, analysis, and description. The most common descriptive research method is the survey, which includes questionnaires, personal interviews, phone surveys, and normative surveys. Developmental research is also descriptive. Through cross-sectional and longitudinal studies, researchers investigate the interaction of diet (e.g., fat and its sources, fiber and its sources, etc.) and life styles (e.g., smoking, alcohol drinking, etc.) and of disease (e.g., cancer, coronary heart disease) development. Observational research and correlational studies constitute other forms of descriptive research. Correlational studies determine and analyze relationships between variables as well as generate predictions. Descriptive research generates data, both qualitative and quantitative, that define the state of nature at a point in time. This chapter discusses some characteristics and basic procedures of the various types of descriptive research.