Current physical activity guidelines for cardiovascular disease (CVD) prevention emphasize volume and intensity rather than common movement behaviors, such as those for everyday living activities. For a study, researchers looked at the links between incident CVD and a machine-learned, accelerometer-measured habit called daily living movement (DLM). In the Women’s Health Initiative OPACH (Objective Physical Activity and Cardiovascular Health) research, older women (n=5,416; mean age, 79±7 years; 33% Black, 17% Hispanic) without prior CVD wore ActiGraph GT3X+ accelerometers for up to 7 days from May 2012 to April 2014 and were followed for physician-adjudicated incident CVD through February 28th, 2020 (n=616 events). Standing and moving in a restricted space, such as doing housekeeping or gardening, was described as DLM. Adjusting for age, race and ethnicity, education, alcohol consumption, smoking, multimorbidity, self-rated health, and physical function, Cox models estimated hazard ratios (HR) and 95% CI. The linearity of the DLM CVD dose-response relationship was investigated using restricted cubic splines. Researchers looked at how age, BMI, Reynolds Risk Score, and race and ethnicity affected effect modification. Across DLM quartiles, adjusted HR (95% CIs) were: 1.00 (reference), 0.68 (0.55–0.84), 0.70 (0.56–0.87), and 0.57 (0.45–0.74); p-trend<0.001. For each hour increment in DLM, the HR (95% CI) was 0.86 (0.80–0.92), with evidence of a linear dose-response connection (P non-linear>0.09). There was no evidence that age, BMI, Reynolds Risk Score, or race and ethnicity affected the results. In older women, having a higher DLM was linked to a lower risk of CVD. Defining the positive effects of physical exercise in terms of typical activities could have aided older persons in increasing their physical activity levels.