Cadence Patterns and cardiovascular disease risk in African-Origin Young Adults: The Modeling the Epidemiologic Transition Study
1
Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
2
Stritch School of Medicine, Loyola University Chicago, Maywood, IL, United States
3
Clincal Research Office, Loyola University Chicago, Maywood, IL, United States
4
Public Health Sciences, Parkinson School of Health Sciences and Public Health, Loyola University Chicago, Maywood, IL, United States
5
Department of Nutrition, Federal University of Sergipe, São Cristóvão, SE, Brazil
6
Department of Physiology, School of Medical Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
7
University Center for Primary Care and Public Health, Unisanté, Lausanne, Switzerland
8
Ministry of Health, Ministry of Health, Victoria, Seychelles
9
Research Centre for Health through Physical Activity, Lifestyle and Sport (HPALS), Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
10
School of Health and Medical Sciences, Faculty of Health, Engineering & Sciences, University of Southern Queensland, Queensland, Australia
11
Solutions for Developing Countries, University of the West Indies, Mona, Kingston, Jamaica
12
Center for Laboratory Medicine, Canton Hospital, St. Gallen, Switzerland
Popul. Med. 2026;8(Supplement Supplement 1):A2986
ABSTRACT
INTRODUCTION:
Low physical activity contributes to cardiometabolic (CM) risk. Step cadence derived from accelerometers can capture ambulatory intensity in free-living adults, yet evidence from low and middle-income settings is limited. We examined cadence patterns and associations between peak cadence indicators and CM risk factors across five African-origin populations in METS.
METHODS:
METS enrolled adults aged 25–45 years from Ghana, South Africa, Jamaica, Seychelles, and the US. Participants with available covariates and valid accelerometry were included (n=2212). Step-defined activity was measured with the Actical accelerometer over 8 days. Minutes per day were summarised across cadence bands, and peak 1-minute, peak 30-minute, and peak 60-minute cadence were derived from rank-ordered minute-by-minute steps. Logistic regression estimated adjusted odds ratios (ORs) per 1 step/min for individual CM risk factors (overweight, high waist circumference, high blood pressure, high triglycerides, high HDL cholesterol, high blood glucose), adjusting for site, sex, age, and smoking. Effect modification by site and sex was assessed with interaction terms.
RESULTS:
Peak cadence differed by site, with higher peak values observed in South Africa (males) and Ghana (females), and the lowest values consistently observed in the US. Most wear time accumulated in zero cadence, with progressively less time in higher cadence bands; males accumulated more minutes than females in purposeful stepping and higher bands. Higher peak 1-, peak 30-, and peak 60-minute cadence were associated with lower adjusted odds of CM risk factors, particularly high waist circumference (aOR peak 1-minute: 0.96, 95% CI: 0.96 to 0.97). Interaction terms between cadence and sex or site were generally not significant.
CONCLUSIONS:
In METS, higher free-living peak step cadence, particularly peak 1-minute cadence, was associated with lower odds of CM risk factors across diverse settings. Cadence may provide a practical, interpretable metric of ambulatory intensity for surveillance and interventions targeting CM risk.
Low physical activity contributes to cardiometabolic (CM) risk. Step cadence derived from accelerometers can capture ambulatory intensity in free-living adults, yet evidence from low and middle-income settings is limited. We examined cadence patterns and associations between peak cadence indicators and CM risk factors across five African-origin populations in METS.
METHODS:
METS enrolled adults aged 25–45 years from Ghana, South Africa, Jamaica, Seychelles, and the US. Participants with available covariates and valid accelerometry were included (n=2212). Step-defined activity was measured with the Actical accelerometer over 8 days. Minutes per day were summarised across cadence bands, and peak 1-minute, peak 30-minute, and peak 60-minute cadence were derived from rank-ordered minute-by-minute steps. Logistic regression estimated adjusted odds ratios (ORs) per 1 step/min for individual CM risk factors (overweight, high waist circumference, high blood pressure, high triglycerides, high HDL cholesterol, high blood glucose), adjusting for site, sex, age, and smoking. Effect modification by site and sex was assessed with interaction terms.
RESULTS:
Peak cadence differed by site, with higher peak values observed in South Africa (males) and Ghana (females), and the lowest values consistently observed in the US. Most wear time accumulated in zero cadence, with progressively less time in higher cadence bands; males accumulated more minutes than females in purposeful stepping and higher bands. Higher peak 1-, peak 30-, and peak 60-minute cadence were associated with lower adjusted odds of CM risk factors, particularly high waist circumference (aOR peak 1-minute: 0.96, 95% CI: 0.96 to 0.97). Interaction terms between cadence and sex or site were generally not significant.
CONCLUSIONS:
In METS, higher free-living peak step cadence, particularly peak 1-minute cadence, was associated with lower odds of CM risk factors across diverse settings. Cadence may provide a practical, interpretable metric of ambulatory intensity for surveillance and interventions targeting CM risk.
| eISSN: | 2654-1459 |
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