1,217 research outputs found

    A simple method for estimating relative risk using logistic regression

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    <p>Abstract</p> <p>Background</p> <p>Odds ratios (OR) significantly overestimate associations between risk factors and common outcomes. The estimation of relative risks (RR) or prevalence ratios (PR) has represented a statistical challenge in multivariate analysis and, furthermore, some researchers do not have access to the available methods. Objective: To propose and evaluate a new method for estimating RR and PR by logistic regression.</p> <p>Methods</p> <p>A provisional database was designed in which events were duplicated but identified as non-events. After, a logistic regression was performed and effect measures were calculated, which were considered RR estimations. This method was compared with binomial regression, Cox regression with robust variance and ordinary logistic regression in analyses with three outcomes of different frequencies.</p> <p>Results</p> <p>ORs estimated by ordinary logistic regression progressively overestimated RRs as the outcome frequency increased. RRs estimated by Cox regression and the method proposed in this article were similar to those estimated by binomial regression for every outcome. However, confidence intervals were wider with the proposed method.</p> <p>Conclusion</p> <p>This simple tool could be useful for calculating the effect of risk factors and the impact of health interventions in developing countries when other statistical strategies are not available.</p

    Self-reported diabetes in older people: comparison of prevalences and control measures

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    OBJECTIVE The objective of this study was to analyze the prevalence of diabetes in older people and the adopted control measures. METHODS Data regarding older diabetic individuals who participated in the Health Surveys conducted in the Municipality of Sao Paulo, SP, ISA-Capital, in 2003 and 2008, which were cross-sectional studies, were analyzed. Prevalences and confidence intervals were compared between 2003 and 2008, according to sociodemographic variables. The combination of the databases was performed when the confidence intervals overlapped. The Chi-square (level of significance of 5%) and the Pearson’s Chi-square (Rao-Scott) tests were performed. The variables without overlap between the confidence intervals were not tested. RESULTS The age of the older adults was 60-69 years. The majority were women, Caucasian, with an income of between > 0.5 and 2.5 times the minimum salary and low levels of schooling. The prevalence of diabetes was 17.6% (95%CI 14.9;20.6) in 2003 and 20.1% (95%CI 17.3;23.1) in 2008, which indicates a growth over this period (p at the limit of significance). The most prevalent measure adopted by the older adults to control diabetes was hypoglycemic agents, followed by diet. Physical activity was not frequent, despite the significant differences observed between 2003 and 2008 results. The use of public health services to control diabetes was significantly higher in older individuals with lower income and lower levels of education. CONCLUSIONS Diabetes is a complex and challenging disease for patients and the health systems. Measures that encourage health promotion practices are necessary because they presented a smaller proportion than the use of hypoglycemic agents. Public health policies should be implemented, and aimed mainly at older individuals with low income and schooling levels. These changes are essential to improve the health condition of older diabetic patients

    Body composition at birth and its relationship with neonatal anthropometric ratios: the newborn body composition study of the INTERGROWTH-21(st) project.

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    Background We aimed to describe newborn body composition and identify which anthropometric ratio (weight/length; BMI; or ponderal index, PI) best predicts fat mass (FM) and fat-free mass (FFM). Methods Air-displacement plethysmography (PEA POD) was used to estimate FM, FFM, and body fat percentage (BF%). Associations between FFM, FM, and BF% and weight/length, BMI, and PI were evaluated in 1,019 newborns using multivariate regression analysis. Charts for FM, FFM, and BF% were generated using a prescriptive subsample (n=247). Standards for the best-predicting anthropometric ratio were calculated utilizing the same population used for the INTERGROWTH-21(st) Newborn Size Standards (n=20,479). Results FFM and FM increased consistently during late pregnancy. Differential FM, BF%, and FFM patterns were observed for those born preterm (34(+0)-36(+6) weeks' gestation) and with impaired intrauterine growth. Weight/length by gestational age (GA) was a better predictor of FFM and FM (adjusted R(2)=0.92 and 0.71, respectively) than BMI or PI, independent of sex, GA, and timing of measurement. Results were almost identical when only preterm newborns were studied. We present sex-specific centiles for weight/length ratio for GA. Conclusions Weight/length best predicts newborn FFM and FM. There are differential FM, FFM, and BF% patterns by sex, GA, and size at birth

    Traumatic atlantoaxial rotatory subluxation in an adolescent: a case report

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    Atlantoaxial rotatory subluxation is rarely caused by trauma in adults. Usually, the treatment of choice is traction using Halo/Gardner-Wells fixation devices for up to six weeks. CASE PRESENTATION: We present the case of a 19-year-old Caucasian woman with traumatic atlantoaxial subluxation. Early reduction three hours after trauma and immobilization using only a soft collar were performed and yielded very good clinical results. CONCLUSION: In the adult population, atlantoaxial subluxation is a rare condition but is severe if untreated. Early treatment implies a non-surgical approach and a good outcome. Conservative treatment is the recommended first step for this condition

    Breastfeeding patterns and exposure to suboptimal breastfeeding among children in developing countries: review and analysis of nationally representative surveys

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    BACKGROUND: Suboptimal breastfeeding is associated with higher mortality among infants and young children in the developing world. We describe patterns in 'exclusive breastfeeding' and 'any breastfeeding' rates and quantify exposure to suboptimal breastfeeding among children aged two years or younger in developing countries. METHODS: We reviewed nationally representative surveys that collected data on breastfeeding rates in 94 developing countries. Surveys were categorized by completeness and comprehensiveness of data. Complete and comprehensive data were analysed with minimum chi-square regression. With a fitting procedure, estimated parameters were used to impute missing observations for incomplete or non-comprehensive surveys. Breastfeeding indicators were calculated and are reported for 135 developing countries by UN region. RESULTS: Amongst infants aged six months or younger in the developing world, the prevalence of exclusive breastfeeding is 39% and the prevalence of no breastfeeding is 5.6%. The prevalence of continued breastfeeding is 86% and 68% for infants and children aged 6–11 and 12–23 months, respectively, in the developing world. Imputation expands population coverage of indicators, especially for infants. Breastfeeding trends are highly linear and estimated parameters defining the age-specific attrition hazard are robust. Survey-reported rates, particularly for exclusive breastfeeding, appear to have systematic upward bias, and exposure estimates must be considered conservative. CONCLUSIONS: Compliance with breastfeeding recommendations in developing countries is low, and more attention should be given to increasing breastfeeding – especially exclusive breastfeeding – and to monitoring trends. Although the introduction of more standardized and better validated survey instruments is desirable, since data coverage, completeness and comprehensiveness are extensive, global exposure assessment is relatively robust. Moreover, the regularity of breastfeeding patterns show existing survey data capture real biological and social phenomena. Our method for the analysis of breastfeeding rates provides a potent tool for summarizing trends, validating observations, translating and extrapolating indicators (as well as projecting and imputing estimates when necessary) and should support more effective child health monitoring
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