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Tran The Trung Department of Endocrinology University of Medicine and Pharmacy HCMC.

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Presentation on theme: "Tran The Trung Department of Endocrinology University of Medicine and Pharmacy HCMC."— Presentation transcript:

1 Tran The Trung Department of Endocrinology University of Medicine and Pharmacy HCMC

2 Cross-sectional Study: Introduction Cross-sectional = prevalence study All measurements are made at once Suitable goal: Prevalence* Describing the variables and their distribution patterns* Associations between variables (then infer cause & effect based on the author hypotheses, not on the design study)

3 Cross-sectional studies Snap shot Measure exposure and outcome variables at one point in time. Main outcome measure is prevalence P = Number of people with disease x at time t Number of people at risk for disease x at time t Prevalence=k x Incidence x Duration

4 Cross-sectional study structure Population  Sample Measurements : Once Variables: characteristics, factors, diseases,… One variable: Prevalence (nominal, categorical variables) Distribution (numeric variables)

5 Cross-sectional study structure Population Sample Sampling

6 Prevalence Numerator: Number of people who have the disease at one point in time Denominator: Number of people (at risk) at that point => Cross-sectional study: the only suitable design to estimate Prevalence

7 Association between variables No risk factor No disease Risk factor Disease Risk factor No disease No risk factor Disease Risk factor = predictor variable Disease = outcome variable Which variables are predictors ? Which are outcomes ? Sample Ex. Age, sex Income, marital status Habit (smoking) Weight

8 Cross-sectional studies - Strengths Useful baseline assessment Generalizable results if population based sample Study multiple outcomes and exposures Immediate outcome assessment and no loss to follow-up, therefore faster, cheaper, easier Can measure prevalence Hypothesis generating for causal links Serial surveys eg, Census

9 Cross-sectional studies - Weaknesses Provide limited information. Cannot establish sequence of events Not for causation or prognosis Look for biological plausibility in causal links Impractical for rare diseases if pop based sample. Could use in rare disease registry. Prone to bias (selection, measurement).

10 Strengths and weaknesses No waiting time Fast & inexpensive No loss of follow-up Prevalence of a disease or risk factor Relations of variables May be the first step in a cohort study Difficulty of establishing causal relationships from data Impractical to study rare disease (can be done on rare disease if sample is collected from high risk or diseased patients). Not measure incidence (no information for prognosis & natural history)

11 Bias in cross-sectional studies Selection Bias Is study population representative of target population? Is there systematic increase or decrease of prevalence? Measurement Bias Outcome Misclassified (dead, misdiagnosed, undiagnosed) Length-biased sampling Cases overrepresented if illness has long duration and are underrepresented if short duration.(Prev = k x I x duration) Risk Factor Recall bias Prevalence-incidence bias RF affects disease duration not incidence eg, HLA-A2

12 Cross-sectional studies - Uses Prevalence used in planning Individual:Pre-treament probability for Rx and Dx Population:Health care services Describe distribution of variables Examine associations among variables Hypothesis generating for causal links Prediction

13 Analyses used in studies Cross- sectional Case-controlCohort PrevalenceYesNo IncidenceNo Yes CorrelationYes RegressionYes ORYes RRNo Yes HRNo Yes SurvivalNo Yes

14 Calculation Prevalence: Disease D = (a + c)/(a+b+c+d) Factor A = (a + b)/(a+b+c+d) Association: OR = ad/bc Factor A Disease D +- +ab -cd

15 EXAMPLE: A CROSS- SECTIONAL STUDY

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17 Abstract The objective of this study was to assess the extent of diabetic control and its associated factors among Vietnamese patients with diabetes mellitus (DM). The study was conducted among 652 outpatients who were recruited at a public general hospital (People Hospital 115) and a private clinic (Medic Center) in Ho Chi Minh City, Vietnam. Median age of participants was 57 years from People Hospital 115, and 60 years for participants from Medic Center. 39% of patients at People Hospital 115 and 33% of patients at Medic Center had Hemoglobin A1c (HbA1c) greater than 8%. However, 55% and 45% of these patients from each facility reported they are in good control... Overall, Vietnamese diabetic patients in this study exhibited poor plasma glucose control. Physician education designed to improve monitoring of glucose levels and diabetic complications, and patient education aimed at raising awareness about actual diabetic control are indicated in this population.

18 Purpose of Study The purpose of this study was to investigate: (a) characteristics of diabetic outpatients in the medical practices of an urban area in Vietnam, (b) factors associated with diabetic control among these patients, and (c) capacities of these patients to self-manage DM.

19 Methods This cross-sectional study was conducted from December 17, 2007 to January 17, 2008 in Ho Chi Minh City, Vietnam. Study participants were diabetic outpatients who visited endocrinologists at a private clinic (Medic Center) and a public hospital (People Hospital 115) during the survey period.

20 Methods General variables: date of birth, sex, anthropometries, family history, and health habits (tobacco smoking and alcohol consumption). DM-related variables: previous visits, year of diagnosis, year medication was initiated, type of DM, glycemic measurements (fasting or casual blood glucose concentration [mg/dL], and HbA1c [%] measured within 6 months), type of DM treatment (diet alone, sulfonylurea, alpha- glucosidase inhibitors, biguanides, thiazolidine derivatives, phenylalanine derivatives, insulin, or other treatments), and the presence or absence of diabetic complications (diabetic retinopathy within the last 12 months, proteinuria, diabetic gangrene, and atherosclerotic disease).

21 Methods HbA1c: with less than 6.5% being recognized as good control and 8.0% or higher as poor control. Hypertension Lipid-related data Participants were interviewed about their perception of well-being, DM-related distress, evaluation of self- management, and perception of diabetic control.

22 Results A total of 658 diabetic patients (257 at People Hospital 115 and 401 at Medic Center) were invited to participate in the study. Of these, 652 patients (253 at People Hospital 115 and 399 at Medic Center) agreed to participate. At People Hospital 115, the median age of participants was 57 years (28-82) and 51.0 % of patients were male. At Medic Center, the median age was 60 years (24-92) and 22.3% of patients were male (Table 1).

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24 Results Median fasting plasma glucose concentration was mg/dL (70-375) at People Hospital 115 and 131 mg/dL (49-441) at Medic Center. Median HbA1c was 7.5% ( ) at People Hospital 115 and 7.3% ( ) at Medic Center.

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29 Summary Cross-sectional study ~ Prevalence study The only design to assess a prevalence. Other statistic can also be calculated in cross-sectional study (depend on the aims of the study), including: comparison (t-test, Chi-square, ANOVA), correlations (Pearson-r, Spearman-rho), regression (linear and logistic OR). But not RR (and HR also)!


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