1
Cross- sectional data suggest that leisure-time physical activity may increase during retirement.
2
Free IGF-I levels were inversely associated with endometrioid adenocarcinoma, consistent with prior cross- sectional data.
3
Longitudinal analyses largely confirmed results observed in the cross- sectional data.
4
Design: Multilevel and spatial analyses of cross sectional data.
5
We then provide an empirical illustration using cross- sectional data.
6
Dyadic, cross- sectional data were analyzed using actor-partner interdependence models.
7
Cross- sectional data can identify associations, not causal relationships.
8
Conclusion: The cross- sectional data suggest an association between symptoms pertaining to the reproductive tract and psychological distress.
9
Cross- sectional data were obtained from MrOS, and longitudinal data (baseline and 8 years) from DHS.
10
Cross- sectional data were collected via questionnaires from a sample of 354 nurses working in Malaysian public hospitals.
11
Cross- sectional data suggest that energy consumption later in the day and during the night is associated with weight gain.
12
Cross- sectional data precluded causal inference.
13
Reference charts were constructed using multilevel statistical analysis and comparisons were made with previously published charts derived from cross- sectional data.
14
Moreover, the cross- sectional data recorded on the prevalence of ASF will help to better rule on the spread of the disease.
15
Cross- sectional data and baseline data from clinical trials and cohort studies for African Americans and non-Hispanic whites with diabetes were included.
16
Methods: Cross sectional data were collected from strengthened maternity registers at 23 facilities over 18 months.
