Abstract

Background

The health benefits of physical activity, including walking, are well-established, but the relationship between daily step count and mortality in hypertensive populations remains underexplored. This study investigates the association between daily step count and both all-cause and cardiovascular mortality in hypertensive American adults.

Methods

We used data from the National Health and Nutrition Examination Survey 2005鈥�2006, including 1,629 hypertensive participants with accelerometer-measured step counts. Cox proportional hazards models and restricted cubic spline regression were employed to assess the associations between daily step count and mortality outcomes. Analyses were adjusted for demographics, lifestyle factors, and comorbidities.

Results

Over an average follow-up of 12.57 years, 370 deaths occurred, of which 177 were due to cardiovascular causes. We observed non-linear associations between daily step count and mortality. Mortality risks were significantly reduced with step counts to 8,250 steps/day for all-cause mortality and 9,700 steps/day for cardiovascular mortality. Beyond these thresholds, the benefits plateaued.

Conclusion

Increasing daily step count is associated with reduced all-cause and cardiovascular mortality in hypertensive individuals, with optimal benefits observed below 8,250 and 9,700 daily steps, respectively. Moderate levels of physical activity provide substantial health benefits, highlighting the importance of setting realistic and attainable activity goals for hypertensive populations.

Introduction

Hypertension, a pervasive chronic condition affecting approximately 122.4听million United States (U.S.) adults, has become a critical public health issue [1]. Often referred to as the 鈥榮ilent killer,鈥� hypertension is responsible for a significant proportion of cardiovascular deaths. In 2021, cardiovascular disease claimed 931,578 lives in the U.S., with 13.4% of these deaths directly attributed to high blood pressure [1]. Furthermore, hypertension鈥檚 economic impact is substantial, with direct and indirect costs projected to rise by $130.4听billion between 2010 and 2030 [2]. Although hypertension management has significantly progressed in recent years [3], ample opportunities for further advancement remain. Consequently, there is imperative to identify effective strategies to delay or prevent undesirable outcomes for hypertensive patients.

The health advantages of physical activity (PA) for hypertensive individuals are well-established [4]. Moderate PA prevents and treats hypertension [5, 6] and reduces the likelihood of adverse cardiovascular and cerebrovascular events and mortality within this demographic [7, 8]. Xiang et al. [9] demonstrated that, in hypertensive adults, moderate-intensity physical activity (MPA) significantly reduces all-cause mortality and cardiovascular events. Similarly, Del Pozo Cruz et al. [10] found linear inverse dose-response relationships between total physical activity and both mortality and cardiovascular disease incidence in this population. Given the challenges some hypertensive patients face in achieving recommended activity levels, accessible and practical forms of PA are particularly valuable. Walking, an easily implemented and accessible form of PA, has gained widespread endorsement. In 2018, the PA guidelines for Americans recommended steps as the fundamental unit of locomotion [11]. The ubiquity of portable smart devices has popularized the daily step count metric within global healthcare systems. Existing evidence highlights the importance of augmenting daily step count to prevent chronic diseases [12,13,14] and premature mortality [15]. This metric effectively encourages adults to achieve recommended PA levels [11, 16].

Despite growing interest, the relationship between daily step count and mortality in hypertensive patients remains underexplored. Further research is needed to determine whether increasing daily step counts can serve as an effective intervention to reduce mortality among hypertensive populations. In particular, identifying an optimal daily step threshold for improving health outcomes in this group is crucial. To bridge this knowledge gap, our study investigates the association between daily step count and both all-cause and cardiovascular mortality among hypertensive U.S. adults, utilizing data from the NHANES 2005鈥�2006. We hypothesize that higher daily step counts are associated with a lower risk of mortality.

Methods

Study setting and population

The non-institutionalized civilian population of the United States is represented by the NHANES, a national survey. As a component of the Centers for Disease Control and Prevention, the National Center for Health Statistics (NCHS) is in charge of conducting the survey [17]. The research procedures for NHANES received authorization from the Ethics Review Committee of NCHS, with all participants supplying their explicit, written consent through signed documents [18]. This analysis, which utilizes de-identified data and does not involve direct participant interaction, is exempt from institutional review board evaluation according to National Institutes of Health policy.

For this research, data were obtained from the NHANES 2005鈥�2006 two-year cycle. The initial sample included 10,348 individuals. From these, we identified 5,563 adults (age鈥夆墺鈥�18), among whom 2,502 were further selected based on a diagnosis of hypertension, with the diagnostic criteria detailed later in the text. Then, 35 pregnant participants, 201 participants with ineligible or incomplete follow-up data, 303 participants with incomplete daily step count data, and 334 participants with incomplete other data, were eliminated. 1, 629 adults with hypertension comprised the final enrolled participants, and the analysis included all the data. Figure听1 depicts a flowchart of our study.

Fig. 1

Flow chart of study participants

Assessment of daily step count

Participants in the research were required to wear an ActiGraph accelerometer (model 7164) on their hip throughout the day for up to 7 days in 2005 and 2006. Non-wear time was determined using an automated algorithm [19], and only participants who had at least one day of valid wear time (i.e., 鈮モ��10听h per day) were included in the analysis. As reported in another study [15], daily step counts (steps per day) were calculated by summing the minute-by-minute steps each participant took over each valid day and determining the median values from the valid days for each participant.

Blood pressure measurement and definition of hypertension

Blood pressure was measured during two separate sessions: at home by a trained research assistant and at a mobile examination clinic by a skilled clinician, with three readings taken during each session. Participants were required to sit quietly for five minutes before measurements were taken. The protocol for calculating average blood pressure excluded the first reading of each session to ensure consistency and accuracy. If only one reading was obtained, that sole reading was used as the average. For diastolic pressure, any reading recorded as zero was not included in the calculation of the average; if all diastolic readings were zero, the average diastolic pressure was recorded as zero. The average of the second and third measurements from each session was then used to establish systolic and diastolic blood pressures.

Hypertension was diagnosed based on the average blood pressure readings meeting any of the following criteria: a systolic blood pressure of 130 mmHg or higher, a diastolic blood pressure of 80 mmHg or higher, a self-reported history of hypertension diagnosed by a physician, or current use of medication to lower blood pressure [20].

Ascertainment of mortality

All-cause mortality was the study鈥檚 primary endpoint, and it was assessed using the National Death Index [21]. Cardiovascular mortality, which served as the secondary endpoint in our study, primarily refers to deaths resulting from cardiac and cerebrovascular diseases. In accordance with the 10th revision of the International Classification of Diseases (ICD-10), the relevant codes corresponding to these diseases encompass I00-I09, I11, I13, I20-I51, and I60-I69.

Definition of covariates

Baseline surveys were utilized to gather data on demographics (age, sex, race, marital status, and education level), status of smoking and alcohol drinking, and personal medical histories (diabetes mellitus, coronary heart disease, congestive heart failure, and stroke). Race was categorized into five groups: Non-Hispanic White, Non-Hispanic Black, Mexican American, and Other. Marital status was categorized into six groups: never married, married, separated, divorced, widowed, and living with partner. Education level was stratified into three levels: 鈥�< high school鈥�, 鈥榟igh school鈥�, and 鈥樷墺high school鈥�. There were three categories for smoking status: 鈥楴ever鈥� (fewer than 100 cigarettes smoked in their lifetime), 鈥楩ormer鈥� (more than 100 cigarettes smoked but no longer do), and 鈥楥urrent鈥� (more than 100 cigarettes and still smoking). Drinking status was divided into three categories: 鈥楴ever鈥� (fewer than 12 drinks), 鈥楩ormer鈥� (at least 12 drinks in a year, but not in the most recent year or had ceased), and 鈥楥urrent鈥�. (at least 12 drinks in their lifetime, with the latest intake within the last year). Diabetes mellitus (DM) was defined based on any of the following criteria: self-reported diagnosis, use of insulin or hypoglycemic medications, hemoglobin A1c (HbA1c) levels of 6.5% or higher, fasting blood glucose (FBG) levels of 7.0 mmol/L or higher, or a 2-hour postprandial glucose (2hPG) level of 11.1 mmol/L or higher [22]. Coronary heart disease (CHD) was diagnosed based on participant reports of a physician鈥檚 confirmation of CHD, myocardial infarction, or angina. Congestive heart failure (CHF) was diagnosed based on participant reports of a physician鈥檚 confirmation of having CHF. Stroke status was similarly determined through self-reported physician diagnoses of stroke or transient ischemic attack.

Physical measurements were recorded, such as height, weight, systolic blood pressure (SBP), and diastolic blood pressure (DBP). The body mass index (BMI) was computed by dividing weight in kilograms by the height in meters squared. Blood specimens were obtained after an 8-hour fast, and the strict protocols outlined in the NHANES Laboratory Medical Technician Procedures Manual were followed to analyze the blood for triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), estimated glomerular filtration rate (eGFR), and HbA1c. Detailed information on specimen collection, processing, quality assurance, and monitoring are described in the section of the biospecimen program in NHANES.

Statistical analysis

Participants were categorized into four groups according to quartiles, including Quartile 1 (daily step count鈥夆墹鈥�4,346), Quartile 2 (4,346鈥�<鈥塪aily step count鈥夆墹鈥�7,319), Quartile 3 (7,319鈥�<鈥塪aily step count鈥夆墹鈥�10,148), and Quartile 4 (daily step count鈥�>鈥�10,148). To compare the baseline characteristics of these groups and determine their differences, continuous variables were reported as mean鈥壜扁�塖E or median (interquartile range), while categorical variables were shown as numbers (percentage, %). Chi-square analysis was employed to compare categorical variables, whereas continuous variables were contrasted using Student鈥檚 t-test for normally distributed data and the Mann-Whitney U-test for data with skewed distributions.

Multivariate Cox regression analyses was performed to examine the associations of daily step count with all-cause and cardiovascular mortality. The daily step count was both evaluated as a continuous variable (per 1,000 steps/day increment) and as a categorical variable split into the four groups mentioned above. Three models were designed to investigate potential associations between predictor and outcome variables: Crude Model, the unadjusted model, did not account for any covariates; Model I controlled for age, sex, and race; and Model II (the fully adjusted model) further adjusted for age, sex, race, marital status, educational level, smoking status, drinking status, and history of DM, CHD, CHF and stroke.

Cumulative Kaplan-Meier curves were constructed, stratified by daily step count quartiles, to depict the occurrence of all-cause and cardiovascular fatalities throughout the follow-up duration. The log-rank test was employed to evaluate differences among quartiles.

Possible non-linear dose-response associations between daily step count and the primary and secondary endpoints were investigated utilizing the multivariate Cox regression with restricted cubic spline (RCS) analyses. The RCS model included 3 knots, chosen based on recommended practices to ensure sufficient flexibility while avoiding overfitting [23]. When non-linear dose-response relationships were present, two-piecewise regression models were employed to assess how these connections changed around the breakpoint. A log-likelihood ratio test was used to contrast segmented and unsegmented regression models in order to determine whether a threshold existed. The transition point linking the segments was determined using a two-step recursive approach, relying on the model exhibiting the highest likelihood. The location of the RCS knot was determined using threshold values identified through a two-piecewise regression model.

Subgroup analyses were executed based on demographic and health attributes: age (鈥�<60鈥� versus 鈥樷墺60鈥�), sex (鈥楳ale鈥� versus 鈥楩emale鈥�), race (鈥楴on-Hispanic White鈥� versus 鈥楴on-Hispanic Black鈥� versus 鈥楳exican American鈥� versus 鈥極ther鈥�), marital status (鈥楴ever married鈥� versus 鈥楳arried/Live with partner鈥� versus 鈥楽eparated/Divorced/Widowed鈥�), educational level (鈥�< High school鈥� versus 鈥樷墺High school鈥�), BMI (鈥�<30鈥� versus 鈥樷墺30鈥�), smoking status (鈥楴ever or former鈥� versus 鈥楥urrent鈥�), drinking status (鈥楴ever or former鈥� versus 鈥楥urrent鈥�), and the presence or lack of DM (鈥楴o or prediabetes鈥� versus 鈥榊es鈥�), CHD (鈥楴o鈥� versus 鈥榊es鈥�), CHF (鈥楴o鈥� versus 鈥榊es鈥�), and stroke (鈥楴o鈥� versus 鈥榊es鈥�). The significance of interaction effects was assessed using the likelihood ratio test. (P-interaction).

Furthermore, to evaluate the association between daily step count and cardiovascular mortality, considering non-cardiovascular mortality as a competing risk, we employed the Fine-Gray test using the tidycmprsk package. We applied the Fine-Gray test to compare the relationship between daily step count and cardiovascular mortality across different step count thresholds, both before and after the identified inflection point.

To mitigate potential reverse causation bias, sensitivity analyses were conducted to examine the consistency of the association between daily step count levels and all-cause and cardiovascular mortality. Participants who died within the first 12 months of follow-up were excluded, as their deaths might reflect pre-existing severe conditions rather than the long-term effects of physical activity. R software 4.2.1 was utilized to conduct the statistical analyses (). The significance of each comparison was assessed using a two-sided P-value cutoff of 0.05.

Results

Baseline characteristics

This study analyzed 1,629 hypertensive adults from the NHANES 2005鈥�2006 dataset (Fig.听1). Among these participants, 55.19% were male, with a median age of 57 years [interquartile range (IQR), 44鈥�69]. The median daily step count was 7319 [interquartile range (IQR), 4346鈥�10148]. Over an average follow-up duration of 150.94 months (approximately 12.57 years), there were 370 deaths (22.71%), of which 177 (10.87%) were due to cardiovascular causes. Baseline characteristics across different daily step count quartiles are detailed in Table听1. A statistically significant decrease in all-cause and cardiovascular mortality was noted among individuals with higher daily step counts (P鈥�&濒迟;鈥�0.05). These participants were typically younger, predominantly male, more often Mexican American, married, and frequent smoker and alcohol consumers. Furthermore, they presented with lower values of BMI, HbA1c, and a lower prevalence of DM, CHD, CHF, stroke, all-cause mortality, and cardiovascular mortality. Conversely, they exhibited higher levels of DBP, TC and eGFR (P鈥�&濒迟;鈥�0.05).

Table 1 Demographic and clinical characteristics among hypertensive U.S. adults according to quartiles of daily step count

Association of daily step count with all-cause and cardiovascular mortality

The Kaplan-Meier survival curves demonstrate significant differences in survival probabilities among the daily step count quartiles. Specifically, individuals in quartile 4 (daily steps鈥�>鈥�10,148) exhibited the highest survival probabilities, indicating a substantially reduced risk for both all-cause (Fig.听2a) and cardiovascular mortality (Fig.听2b), with the differences achieving statistical significance (Log-rank P鈥�&濒迟;鈥�0.01).

Fig. 2

Kaplan-Meier survival curve for all-cause (a) and cardiovascular (b) mortality by daily step count quartiles

Further, multivariate Cox regression (Table听2) assessed the impact of daily step count on all-cause and cardiovascular mortality. Model II showed that an increase of 1,000 steps per day was associated with a HR of 0.90 (95% CI: 0.87, 0.93, P鈥�<鈥�0.05) for all-cause mortality, and an HR of 0.92 (95% CI: 0.87, 0.97, P鈥�<鈥�0.05) for cardiovascular mortality. When treated as a categorical variable, the HRs for all-cause mortality for quartiles 2, 3, and 4 were 0.64 (95% CI: 0.50, 0.83), 0.43 (95% CI: 0.31, 0.60), and 0.46 (95% CI: 0.31, 0.67), respectively, demonstrating a significant trend (P for trend鈥�&濒迟;鈥�0.01). For cardiovascular mortality, the respective HRs were 0.55 (95% CI: 0.38, 0.81), 0.46 (95% CI: 0.29, 0.74), and 0.46 (95% CI: 0.26, 0.81) (P for trend鈥�&濒迟;鈥�0.01). The initial crude model included no covariates, Model I was adjusted for age, sex, and race, while Model II included comprehensive adjustments for age, sex, race, marital status, educational level, smoking status, drinking status, and history of DM, CHD, CHF, and stroke. Each progressive model refinement underscored the robust association between increased daily step counts and decreased mortality risks.

Table 2 Multivariate logistic regression analysis of daily step count for all-cause or cardiovascular mortality among hypertensive U.S. adults

Detection of non-linear dose-response relationships

The RCS regression was utilized to explore the dose-response relationship between daily step count and mortality due to all causes and cardiovascular issues, adjusting for all variables in Model II. The RCS results showed that there were significant non-linear dose-response associations between daily step count and both all-cause mortality (Fig.听3a) and cardiovascular mortality (Fig.听3b) after controlling for all factors in Model II (P for non-linearity鈥�&濒迟;鈥�0.01).

Fig. 3

Association of daily step count with the all-cause (a) and cardiovascular (b) mortality performed by restricted cubic spline analysis. Results were adjusted for age, sex, race, marital status, educational level, smoking status, drinking status, and history of DM, CHD, CHF and stroke. Red lines represent the HR (hazard ratio), and red transparent areas represent the 95% confidence intervals

Subsequent analysis employed a two-piecewise Cox proportional hazards model, as detailed in Table听3. The derived threshold values were 8,250 steps per day for all-cause mortality and 9,700 steps per day for cardiovascular mortality. Below these thresholds, each increment of 1,000 steps per day was significantly associated with decreased adjusted HRs for all-cause (HR 0.86; 95% CI 0.82, 0.90; P鈥�<鈥�0.01) and cardiovascular mortality (HR 0.88; 95% CI 0.82, 0.93; P鈥�&濒迟;鈥�0.01). Above these thresholds, the relationship for all-cause mortality plateaued (HR 1.00; 95% CI 0.93, 1.08; P鈥�=鈥�0.91), and for cardiovascular mortality, a non-significant reversal in trend was observed (HR 1.07; 95% CI 0.94, 1.20; P鈥�=鈥�0.31). The log-likelihood ratio tests confirmed the statistical significance of these findings (P鈥�<鈥�0.01 for all-cause and P鈥�=鈥�0.03 for cardiovascular mortality).

Table 3 Two-piecewise Cox regression analysis of daily step count between all-cause and cardiovascular mortality

Subgroups analysis

Subgroup analysis demonstrated consistent inverse associations between daily step count and both all-cause (Fig.听4a) and cardiovascular mortality (Fig.听4b) across all evaluated subgroups. A notable interaction effect was observed in the CHF stratification concerning the link between daily step count and cardiovascular mortality (P for interaction鈥�=鈥�0.04), indicating a significantly stronger association among individuals with a history of CHF. For this subgroup, each increase of 1,000 daily steps was associated with a more pronounced reduction in cardiovascular mortality risk (HR: 0.79; 95% CI: 0.67, 0.94; P鈥�=鈥�0.01). Conversely, the reduction was less pronounced among those without a history of CHF (HR: 0.93; 95% CI: 0.88, 0.98; P鈥�=鈥�0.01). No significant interaction effects were observed for other stratification variables, confirming the robustness of daily step count as a predictor of mortality risk due to all causes and cardiovascular events among hypertensive adults, irrespective of demographic and clinical characteristics.

Fig. 4

Association of daily step count (per 1000 steps/day) with all-cause mortality (a) and cardiovascular mortality (b) in various subgroups. Results are expressed as multivariable-adjusted HRs after controlling covariates that include age, sex, race, marital status, educational level, smoking status, drinking status, and history of DM, CHD, CHF and stroke, except for the variable used in each specific subgroup analysis, which was not adjusted for in its own analysis. The results are weighted based on the survey. Abbreviation: N, number; HR, hazard ratio; CI, confidence; DM, diabetes mellitus; CHD, coronary heart disease; CHF, congestive heart failure

Competing risks analysis

To assess the impact of daily step count on cardiovascular mortality among U.S. adults with hypertension, participants were categorized into two groups: those with fewer than 9,700 steps per day and those with 9,700 or more. Non-cardiovascular mortality was treated as a competing event, and the Fine-Gray competing risk model was applied. At 12, 24, 36, 60, and 120 months, cumulative incidences of cardiovascular mortality for the <鈥�9,700 steps group were 0.17%, 1.20%, 2.22%, 3.93%, and 9.23%, respectively; for the 鈮モ��9,700 steps group, incidences were 0.00%, 0.22%, 0.65%, 1.09%, and 2.18% (P鈥�<鈥�0.01) (Supplementary Table 1). Supplementary Fig.听1 illustrates higher cumulative cardiovascular mortality in the <鈥�9,700 steps group compared to the 鈮モ��9,700 steps group (Fine-Gray P鈥�&濒迟;鈥�0.01). Similarly, cumulative incidences of non-cardiovascular mortality at the same intervals were higher in the <鈥�9,700 steps group: 0.43%, 0.94%, 1.97%, 3.85%, and 9.40%, versus 0.00%, 0.00%, 0.22%, 0.44%, and 3.49% in the 鈮モ��9,700 steps group (Fine-Gray P鈥�<鈥�0.01; see Supplementary Table 1).

Sensitivity analysis

To assess the robustness of our findings, we excluded participants who died within the first 12 months and repeated the primary analyses. The associations between daily step count鈥攂oth as a continuous variable (per 1,000 steps/day increase) and across quartiles鈥攁nd all-cause and cardiovascular mortality remained consistent, as detailed in Supplementary Table 2. Additionally, the non-linear relationships between daily step count and both mortality outcomes showed no significant changes after this exclusion, as illustrated in Supplementary Fig.听2.

Discussion

To our knowledge, this study is the first to elucidate the relationship between daily step count and both all-cause and cardiovascular mortality in a large cohort of hypertensive patients. Our findings indicate that a higher daily step count is significantly associated with a reduced risk of all-cause and cardiovascular mortality, independent of demographic factors, lifestyle, clinical assessments, biochemical markers, and comorbidities. Furthermore, we identified non-linear dose-response relationships, with mortality risks decreasing substantially at daily step counts below 8,250 and 9,700 steps per day for all-cause and cardiovascular mortality, respectively. Subgroup analysis demonstrated consistent inverse associations across all evaluated groups, with a more pronounced reduction in cardiovascular mortality observed in individuals with a history of CHF. Other stratification variables did not show significant interaction effects, supporting the robustness of daily step count as a protective factor in hypertensive populations. These results offer new insights into how PA, as measured by daily step count, influences mortality risk in individuals with hypertension.

In this investigation, we expand on existing knowledge by focusing on a cohort of hypertensive patients, addressing a key gap in understanding the relationship between daily step count and the risk of both all-cause and cardiovascular mortality. Our findings are consistent with previous studies that highlight the importance of PA in managing hypertension and reducing mortality risk [11, 24]. However, our research is distinct in that it specifically examines daily step count, rather than other dimensions of PA such as frequency, intensity, or duration, which have been the focus of previous studies.

By concentrating on hypertensive patients, this study makes a significant contribution to the literature, given that hypertension is a major risk factor for both cardiovascular disease and all-cause mortality [25]. In line with our findings, earlier research has demonstrated that increased daily step counts are associated with lower all-cause mortality across various populations [13, 26, 27], including the general public [15]. While prior studies have examined the benefits of PA in reducing the incidence of major cardiovascular diseases [28], our study is the first to specifically explore the relationship between daily step count and cardiovascular mortality in hypertensive patients. The observed association between daily step count and reduced mortality risk may be attributed to improvements in cardiovascular health through lowered blood pressure, enhanced circulation, and a healthy heart rate [24]. Additionally, increased PA can contribute to weight loss, which is crucial for managing obesity鈥攁 common risk factor for both hypertension and cardiovascular disease [11]. Regular PA may also help reduce stress levels and improve mental health, further benefiting cardiovascular health and lowering mortality risks [11].

Our study demonstrates a non-linear dose-response relationship between daily step count and mortality, suggesting that beyond a certain threshold, the health benefits of additional steps begin to diminish. Specifically, we found that optimal health outcomes occur at approximately 8,250 steps per day for all-cause mortality and around 9,700 steps per day for cardiovascular mortality. These thresholds are slightly lower than the widely recommended 10,000 steps per day for general health [29] but are consistent with other studies that also report a non-linear association. For example, Banach et al. observed that a 1,000-step increase was associated with a 15% reduction in all-cause mortality, with diminishing benefits beyond 9,000鈥�10,000 steps per day [30]. Similarly, a meta-analysis from Jayedi et al. reported a strong inverse relationship between daily step count and all-cause mortality, with the risk reduction plateauing between 7,000 and 10,000 steps per day [31]. This mirrors the non-linear pattern identified in our study, where the health benefits of additional steps taper off after reaching a certain threshold. Although previous research has not focused on the specific relationship between step count and cardiovascular mortality in hypertensive populations, Inoue et al. showed that even walking 8,000 steps just 1鈥�2 days per week resulted in significant reductions in both all-cause and cardiovascular mortality [32]. Additionally, Ahmadi et al. found that 9,000鈥�10,500 steps per day were the optimal range for reducing both mortality and cardiovascular disease incidence in the UK population [33]. While their study approached the issue from a different perspective, the non-linear trend they observed aligns with our findings, reinforcing that moderate PA can yield substantial health benefits without necessarily meeting the 10,000-step target. The lower step count thresholds observed in our research, as well as in other studies, may be due to the heightened sensitivity of hypertensive individuals and other specific populations to PA [24, 34]. These groups likely experience amplified improvements in vascular function and blood pressure regulation with smaller amounts of exercise. As a result, they can achieve significant health benefits with moderate PA without necessarily reaching the 10,000-step target. Additionally, hypertensive and other high-risk populations often have a higher baseline mortality risk compared to their normotensive counterparts, which could lead to more pronounced risk reductions as their activity levels increase incrementally 鈥� [35]. Therefore, the optimal daily step count for health benefits may vary depending on individual factors such as age, sex, and pre-existing health conditions.

In addition to our primary findings, we observed significant interactions between daily step count and cardiovascular mortality in patients with a history of CHF. The negative association between step count and cardiovascular mortality was particularly strong in this subgroup, suggesting that individuals with CHF may experience greater cardiovascular benefits from moderate increases in physical activity. According to the 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure and the 2023 Scientific Statement from the AHA/ACC, exercise training鈥攖ypically comprising 30听min of moderate-intensity aerobic activity (e.g., walking or cycling) 5 days per week (鈮モ��150听min per week) and at least 2 days per week of muscle-strengthening exercises鈥攊s recommended for patients with CHF who are able to participate, as it improves functional status, exercise performance, and quality of life [36, 37]. Moreover, previous studies have shown that regular physical activity is associated with a lower lifetime risk of CHF and improved cardiac structure and function [38,39,40,41]. This may explain why patients with CHF gain more pronounced benefits from increasing their daily step count. This finding underscores the importance of developing tailored physical activity recommendations for individuals with CHF, to optimize cardiovascular outcomes.

Our study has several notable strengths. To our knowledge, this is the first study to examine the relationship between daily step count and both all-cause and cardiovascular mortality in a large cohort of hypertensive individuals. The large sample size, use of nationally representative data from NHANES, and the extended follow-up period of over 12 years enhance the robustness and generalizability of our findings. Additionally, we accounted for a broad range of potential confounders, strengthening the validity of the observed associations between daily step count and mortality. However, certain limitations should be acknowledged. First, some baseline characteristics were collected via questionnaires or interviews, which introduces the possibility of recall bias. Secondly, although we adjusted for numerous covariates, it remains difficult to account for all potential confounders. Thirdly, our study did not capture key aspects of physical activity beyond step count, such as type, intensity, duration, or frequency, all of which may influence health outcomes. Fourthly, while some studies using NHANES data have included broader timeframes, we restricted our analysis to the 2005鈥�2006 cycle because it was the only cycle with validated step count data (PAXSTEP). Although this approach avoided potential inaccuracies associated with data imputation, it limited our sample size and follow-up period, which may affect the generalizability of our findings. Moreover, reverse causation may influence the results, as individuals in better health might naturally be more active. As such, randomized controlled trials are needed to verify whether increasing daily step count can causally reduce mortality risk in hypertensive patients.

Conclusion

This study demonstrates a significant, non-linear association between daily step count and mortality risk in hypertensive adults, with optimal benefits observed below 8,250 steps for all-cause mortality and 9,700 steps for cardiovascular mortality. Our findings suggest that even moderate increases in daily steps can substantially reduce mortality risk, underscoring the importance of achievable PA goals for hypertensive individuals. These results support the value of promoting daily step count as a simple, effective tool for improving health outcomes in this population. Future research should explore the causal relationships and additional dimensions of PA.