Tran The Trung

Department of Endocrinology

University of Medicine and Pharmacy HCMC

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)

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 tNumber of people at risk for disease x at time t

Prevalence=k x Incidence x Duration

Cross-sectional study structure

• Population Sample• Measurements : Once• Variables: characteristics, factors, diseases,…

• One variable:• Prevalence (nominal, categorical variables)• Distribution (numeric variables)

Cross-sectional study structure

Population

Sample

Sampling

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

Association between variables

No risk factorNo disease

Risk factorDisease

Risk factorNo disease

No risk factorDisease

Risk factor = predictor variable

Disease = outcome variable

Which variables are predictors ?

Which are outcomes ?

Sample

Ex. Age, sex

Income, marital status

Habit (smoking)

Weight

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

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).

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)

Bias in cross-sectional studiesSelection 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

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

Analyses used in studies

Cross-sectional

Case-control Cohort

Prevalence Yes No No

Incidence No No Yes

Correlation Yes Yes Yes

Regression Yes Yes Yes

OR Yes Yes Yes

RR No No Yes

HR No No Yes

Survival No No Yes

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

+ -

+ a b

- c d

EXAMPLE: A CROSS-SECTIONAL STUDY

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.

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.

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.

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).

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.

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).

Results • Median fasting plasma glucose concentration was 123.5

mg/dL (70-375) at People Hospital 115 and 131 mg/dL (49-441) at Medic Center.

• Median HbA1c was 7.5% (5.2-16.2) at People Hospital 115 and 7.3% (5.0-13.4) at Medic Center.

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)!