In some situations two sequential crosssectional surveys are planned; frequently the first crosssectional survey is to establish a preintervention baseline estimate, and then after a period of time (usually 15 years), a second crosssectional survey (“followup” survey) is performed to assess the estimated impact of interventions. This approach to sample size calculation requires a number of assumptions and preferences for certain values. In the calculations below it is assumed that the sample size in each survey will be the same.
Estimates and preferences are needed for:
p_{1} The estimated proportion with disease or intervention at baseline survey
p_{2} The estimated proportion with disease or intervention at followup survey
DEFF The estimated design effect  here it is assumed the DEFF will be the same for both surveys
α Level of significance (“alpha”), usually .05 or 5% (corresponds with 95% confidence interval)
1 β Power, usually .8 (80%) or .9 (90%)
The formula is:
where
and when sample sizes are to be equal
q_{1} = 1 – p_{1}
q_{2} = 1 – p_{2}
Z_{}_{/2} is the Zvalue for the level of significance
Z_{1}_{} is the Zvalue for the Power
The most common Zvalues for the level of significance and Power are provided in Tables 1 and 2, respectively.
(Gorstein J, Sullivan KM, Parvanta I, Begin F. Indicators and methods for crosssectional surveys of vitamin and mineral status of populations. Micronutrient Initiative (Ottawa) and Centers for Disease Control and Prevention (Atlanta), May 2007, pg 31).
Table 1 Twosided Zvalues () for various significance levels
Significance level (α)

2sided Zvalue

.01

2.576

.05

1.960

.10

1.645

Table 2 Onesided Zvalues (Z_{1}_{}) for various Power (1 β) levels
β value

Power (1 β)

1sided Zvalue

.01

.99

2.326

.05

.95

1.645

.10

.90

1.282

.20

.80

0.842

Example: A country is going to begin fortifying flour with iron and estimate the baseline prevalence of anemia to be 50% in women of childbearing age. They estimate that iron fortification of flour will lower the prevalence in this group to 40%.
Example:
p_{1} = .50, q_{1} = .50
p_{2} = .40, q_{2} = .60
α = .05, therefore = 1.96
β = .20, therefore = .842
DEFF = 2
Need to calculate . For equal sample sizes:
,
The sample size would be 776 individuals in for each crosssectional survey, i.e., 776 for the baseline survey and 776 in the followup survey. 