Measurement of physical activity in urban and rural South African adults: a comparison of two self-report methods

Abstract

Background: Due to the large mortality from inactivity-related non-communicable diseases in low- and middle- income countries, accurate assessment of physical activity is important for surveillance, monitoring and understanding of physical (in)activity epidemiology in many of these countries. Research on relative performance of self-report physical activity instruments commonly used for epidemiological research in Africa have rarely been reported. The present study compared estimates of physical activity measured with the International Physical Activity Questionnaire - Short Form (IPAQ-SF) and the Baecke Physical Activity Questionnaire (BPAQ) among urban and rural black South African adults.

Methods: Self-reported physical activity data using the IPAQ-SF and BPAQ were collected from a representative sample of 910 urban and rural black South African adults (age = 59.2 ± 9.5 years, 69.7 % women) participating in the 2015 wave of the Prospective Urban and Rural Epidemiological (PURE) study in the North West Province of South Africa. Between-method relationships (pearson correlations [r] and intraclass correlation coefficients [ICCs]) and agreements (Bland-Altman mean difference with 95 % limits of agreement and Kappa coefficient [k]) of IPAQ-SF and BPAQ variables were estimated. Sensitivity and specificity of the BPAQ relative to the IPAQ-SF to classify individuals according to the international guidelines for sufficient physical activity were calculated using chi-square statistics.

Results: Correlations between IPAQ-SF scores and BPAQ indices were small (r = 0.08-0.18; ICCs = 0.09-0.18) for BPAQ leisure and sport indices, moderate-to-large for work index (r = 0.42-0.59; ICCs = 0.40-0.62) and total physical activity index (r = 0.52-0.60; ICCs = 0.36-0.51). Between methods mean difference for total physical activity was large (1.85 unit), and agreement in physical activity classifications was poor to moderate (k = 0.16-0.44). The sensitivity of the BPAQ to identify sufficiently active people from the IPAQ-SF was very good (98 %), but its specificity to correctly classify insufficiently active people was weak (23 %).

Conclusion: Notable disparities in physical activity estimates between methods suggest that utilization of IPAQ-SF and BPAQ for surveillance and epidemiology studies in Africa should depend on research questions and population to be studied. Future studies with objective measures are needed to confirm the relative validity between the two instruments.

Keywords: Baecke physical activity questionnaire; Epidemiology; International physical activity questionnaire; Low-and middle-income countries; Public health guidelines; Surveillance.

Fig. 1

Bland-Altman plot for total physical activity from the Baecke and IPAQ-SF for overall Sample (Mean Difference: 1.85 +/− 2SD = 0.79 to 2.91)

Fig. 2

Bland-Altman plot for total physical activity from the Baecke and IPAQ-SF for rural Sample (Mean Difference: 1.78 +/− 2SD = 0.67 to 2.90)

Fig. 3

Bland-Altman plot for total physical activity from the Baecke and IPAQ-SF for urban sample (Mean Difference: 1.95 +/− 2SD = 1.01 to 2.89)