Abstract
Aim
To investigate the effect of different physical activity patterns on obesity.
Materials and methods
Data from adults aged 17–79 years were extracted from the Hong Kong Territory‐Wide Physical Fitness Survey conducted in 2011–2012 and 2021–2022. Moderate to vigorous physical activity (MVPA) patterns were collected through questionnaires and categorized as inactive (no MVPA ≥10 min), insufficiently active (<150 min MVPA/week), weekend warriors (≥150 min MVPA/week from 1 to 2 days) and regularly active (≥150 min MVPA/week from ≥3 days). The association between these activity patterns with obesity risk and body fat percentage was analysed.
Results
This study included 9863 obesity data (including valid waist circumference and body mass index) and 7496 body fat data. Compared with the inactive group, the weekend warriors and regularly active individuals had lower risks of general and abdominal obesity, as well as reduced body fat. Furthermore, individuals who were insufficiently active but engaged in ≥3 days of MVPA showed significantly lower body fat and obesity risk than their inactive counterparts.
Conclusion
Engaging in physical activity even once or twice a week can positively impact weight control.
Keywords: body fatness, body mass index, exercise frequency, obesity, waist circumference, weekend warrior
1. INTRODUCTION
The World Health Organization (WHO) recommends that adults engage in 150–300 min of moderate or 75–150 min of vigorous physical activity per week 1 to improve outcomes such as weight control and adiposity. 1 However, these guidelines do not specify the frequency of exercise sessions per week. Thus, whether spreading activity across multiple days or concentrating it into 1 or 2 days would yield similar or different effects on obesity remains unclear.
The ‘weekend warrior’ pattern, where individuals complete the recommended physical activity in just one or two sessions per week, has been less studied. The health benefits of this physical activity pattern were first described in 2004. Lee et al. discovered that compared with inactive men, weekend warriors reduced all‐cause mortality by 15%, according to data from the Harvard Alumni Health Study. 2 A meta‐analysis showed that risk reductions for all‐cause mortality were similar between weekend warriors and those with regularly active patterns. 3 Regarding obesity, two cross‐sectional studies reported no association between weekend warrior activity patterns and a reduced risk of abdominal obesity. 4 , 5 Moreover, the literature lacks a comprehensive assessment of obesity using body mass index (BMI) and adiposity. Recent recommendations suggest combining BMI with waist circumference for a more accurate assessment of obesity than using either measure alone. 6 Therefore, a comprehensive investigation is needed to reveal the relationship between weekend warrior activity patterns and obesity, such as the combination of high BMI and waist circumference and the inclusion of body adiposity measurement.
The 2018 Physical Activity Guidelines Advisory Committee conducted a systematic review that provided strong evidence supporting the relationship between higher levels of moderate‐to‐vigorous physical activity (MVPA) and reduced weight gain in adults. 7 This relationship appears to be most significant when individuals engage in physical activity for more than 150 min/week. 7 Building on this knowledge, we hypothesized that weekend warrior and regularly active patterns may reduce obesity risk similarly because of comparable energy expenditure. Using data from the Hong Kong Territory‐Wide Physical Fitness Survey, 8 , 9 this study aimed to examine the associations between MVPA patterns and obesity, and explore how factors, such as frequency, intensity and duration, influence obesity risk.
2. METHODS
2.1. Study design and dataset description
This cross‐sectional study analysed data from the Hong Kong Territory‐Wide Physical Fitness Survey conducted by the Leisure and Cultural Services Department in 2011–2012 and 2021–2022. Data were collected via face‐to‐face questionnaires and physical fitness assessments using consistent methods to measure waist circumference and BMI. Furthermore, both surveys used the same questionnaire to assess physical activity patterns. For adiposity assessment, we only included data from the 2021–2022 survey, which collected body fat measurements using a bioelectrical impedance device. In addition, both surveys employed a robust stratified and random sampling method across 18 districts, as previously described. 8 , 9 The study included adults aged 17–79, and certified fitness assessors from the Physical Fitness Association of Hong Kong conducted assessments. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines. 10
2.2. Obesity assessments
Abdominal obesity was classified using the International Diabetes Federation's criteria for the Asian population 11 (waist circumferences ≥90 cm for men and ≥80 cm for women). Waist circumference measurements were obtained using Gulick tape, following WHO guidelines. 12 General obesity was defined by a BMI ≥25 kg/m2 according to WHO criteria for Asian adults. 13 Participants with abdominal and general obesity were included in the analysis.
2.3. Body adiposity assessments
Body fat percentage was measured using a multifrequency bioelectrical impedance analyser (MC780; Tanita). Participants stood on footpads with bare feet and held the handgrip with both hands. They wore minimal clothing and cleaned their feet with alcohol before the test to minimize potential interference. A previous study showed a significant correlation between body fat percentage measured using Tanita MC780 and the gold standard method (dual‐energy X‐ray absorptiometry) (r = 0.852, p < 0.001). 14 Furthermore, the intraclass correlation coefficient was calculated to be 0.84, which further supports the reliability of the Tanita MC780 in assessing body fat percentage. 14
2.4. Physical activity assessment
The primary variable in this study was physical activity patterns. Physical activity was categorized into four patterns: inactive, insufficiently active, weekend warrior and regularly active. The inactive pattern refers to individuals who do not engage in any moderate or vigorous‐intensity physical activity. An insufficiently active pattern is characterized by individuals participating in MVPA for less than 150 min/week. The weekend warrior pattern entails individuals who engage in at least 150 min/week of MVPA but only one or two weekly sessions. Finally, the regularly active pattern encompassed individuals who engaged in at least 150 min/week of MVPA from three or more sessions weekly.
We used four questions to gather information on the frequency and weekly duration of MVPA and vigorous‐intensity physical activity (VPA). The complete questionnaire is provided in Data S1, Supplementary 3. To assess the participants' physical activity levels, we first asked them about the number of days in a typical week that they engaged in MVPA and VPA for at least 10 min at a time. If the participants reported engaging in MVPA and VPA, we inquired about the amount of time they spent on these activities weekly. Examples of MVPA and VPA were provided to the participants to ensure clarity and understanding. In addition, a 0–10 Rating of Perceived Exertion (RPE) scale was used to help participants better identify the intensity levels of the activities. In both surveys, we defined vigorous intensity as an RPE rating of 8–9 and moderate intensity as an RPE rating of 4–7.
2.5. Covariates
Trained and certified fitness assessors collected information from the participants regarding various covariates. These variables included sex, age, educational level, household income, smoking status, hypertension and sleep quality. Education was categorized into primary, secondary and post‐secondary levels. Household incomes in Hong Kong Dollars were divided into eight categories: (a) ≤9999; (b) 10,000–19,999; (c) 20,000–29,999; (d) 30,000–39,999; (e) 40,000–49,999; (f) 50,000–59,999; (g) 60,000–99,999; and (h) ≥100,000. Smoking status was classified as never smoker, quit smoking for more than 6 months, and current smoker. Sleep quality was rated on a 1–5 scale (1: very good, 2: good, 3: average, 4: bad, 5: very bad) over the past month. Hypertension was defined using the 2020 International Society of Hypertension Global Hypertension Practice Guidelines (systolic blood pressure ≥140 mmHg and diastolic blood pressure ≥90 mmHg). 15
2.6. Statistical analyses
Data analysis was conducted in January 2024. Logistic regression models were used to investigate the relationship between physical activity patterns and obesity. In addition, a generalized linear model (GLM) was used to examine the association between physical activity patterns and total body fat percentage. Logistic regression and GLM analyses consisted of three models. Model 1 did not include adjustments or covariates. In Model 2, we adjusted for demographic covariates such as sex, age, education and household income. In Model 3, we further adjusted for smoking status, hypertension status and sleep quality in addition to demographic covariates. Furthermore, individuals with missing values for physical activity patterns, waist circumference, BMI and body fat percentage were excluded from the final analysis. The inactive group served as the reference group in logistic regression and GLM analyses. Subgroup analyses by sex and age were conducted to explore their influences on physical activity patterns, obesity and body adiposity. The results were presented using odds ratios and 95% confidence intervals for the logistic regression and beta coefficients and 95% confidence intervals for the GLM. All statistical analyses were conducted using SPSS software (version 27; IBM Corp.). Statistical significance was set at a p‐value of <0.05.
3. RESULTS
3.1. Characteristics of study participants
The dataset included 9994 individuals from two collection periods: April 2011 to January 2012 and August 2021 to December 2022. After excluding incomplete and invalid data, 9863 individuals with valid obesity data (including waist circumference and BMI) and 7496 with valid body fat data were analysed. Table 1 presents the participants' characteristics.
TABLE 1.
Participants' characteristics.
| Characteristics | Inactive | Insufficiently active | Weekend warrior | Regularly active |
|---|---|---|---|---|
| Sex, n (%) | ||||
| Female | 1676 (67.4) | 2377 (61.6) | 330 (52.7) | 1628 (56.3) |
| Male | 810 (32.6) | 1481 (38.4) | 296 (47.3) | 1265 (43.7) |
| Age group, n (%) | ||||
| 17–19 | 10 (0.4) | 58 (1.5) | 10 (1.6) | 69 (2.4) |
| 20–39 | 480 (19.3) | 1174 (30.4) | 222 (35.5) | 602 (20.8) |
| 40–59 | 1186 (47.7) | 1750 (45.4) | 247 (39.5) | 1039 (35.9) |
| 60–69 | 536 (21.6) | 594 (15.4) | 103 (16.5) | 694 (24.0) |
| 70–79 | 274 (11.0) | 282 (7.3) | 44 (7.0) | 489 (16.9) |
| Waist circumference conditions, n (%) | ||||
| Normal | 1553 (62.5) | 2692 (69.8) | 455 (72.7) | 2012 (69.5) |
| Abdominal obesity | 933 (37.5) | 1166 (30.2) | 171 (27.3) | 881 (30.5) |
| Waist circumference, range of quartile, cm | ||||
| First quartile | 53.0–72.0 | 51.0–71.0 | 55.5–72.0 | 54.5–72.7 |
| Second quartile | 72.2–79.1 | 71.1–78.5 | 72.2–78.0 | 72.8–79.1 |
| Third quartile | 79.2–87.5 | 78.6–86.0 | 78.1–85.9 | 79.2–86.3 |
| Fourth quartile | 87.6–123.5 | 86.1–126.0 | 86.0–113.2 | 86.4–123.0 |
| BMI conditions, n (%) | ||||
| Underweight (BMI <18.5) | 151 (6.1) | 221 (5.7) | 38 (6.1) | 101 (3.5) |
| Normal (BMI 18.5–22.9) | 1076 (43.3) | 1764 (45.7) | 287 (45.8) | 1298 (44.9) |
| Overweight (BMI 23–24.9) | 481 (19.4) | 813 (21.1) | 143 (22.8) | 672 (23.2) |
| Obese I (BMI 25–29.9) | 627 (25.2) | 871 (22.6) | 128 (20.4) | 713 (24.7) |
| Obese II (BMI ≥30.0) | 150 (6.0) | 187 (4.8) | 30 (4.8) | 108 (3.7) |
| BMI, range of quartile | ||||
| First quartile | 13.7–20.8 | 14.6–20.8 | 16.3–20.8 | 14.9–21.2 |
| Second quartile | 20.9–23.0 | 20.9–22.9 | 20.9–22.9 | 21.3–23.1 |
| Third quartile | 23.1–25.7 | 23.0–25.3 | 23.0–25.1 | 23.2–25.3 |
| Fourth quartile | 25.8–42.3 | 25.4–46.7 | 25.2–40.6 | 25.4–43.2 |
| Body fat percentage, range of quartile | ||||
| First quartile | 5.3–23.5 | 3.0–22.4 | 3.0–20.3 | 3.0–21.0 |
| Second quartile | 23.5–28.9 | 22.4–27.9 | 20.4–26.0 | 21.0–27.1 |
| Third quartile | 28.9–34.4 | 27.9–33.4 | 26.1–31.7 | 27.2–32.9 |
| Fourth quartile | 34.5–60.7 | 33.4–63.1 | 31.8–52.7 | 33.0–61.3 |
| Education level, n (%) | ||||
| Primary school or below | 453 (18.4) | 302 (7.9) | 34 (5.5) | 420 (14.6) |
| Secondary school | 1286 (52.3) | 1516 (39.7) | 212 (34.1) | 1218 (42.5) |
| Post‐secondary | 720 (29.3) | 2000 (52.4) | 376 (60.5) | 1231 (42.9) |
| Household income, HKD; n (%) | ||||
| ≤9999 | 451 (18.1) | 538 (13.9) | 74 (11.8) | 498 (17.2) |
| 10,000–19,999 | 512 (20.6) | 654 (17.0) | 79 (12.6) | 424 (14.7) |
| 20,000–29,999 | 437 (17.6) | 623 (16.1) | 108 (17.3) | 386 (13.3) |
| 30,000–39,999 | 269 (10.8) | 453 (11.7) | 81 (12.9) | 249 (8.6) |
| 40,000–49,999 | 175 (7.0) | 303 (7.9) | 55 (8.8) | 174 (6.0) |
| 50,000–59,999 | 28 (1.1) | 38 (1.0) | 6 (1.0) | 26 (0.9) |
| 60,000–99,999 | 122 (4.9) | 357 (9.3) | 67 (10.7) | 193 (6.7) |
| ≥100,000 | 41 (1.6) | 167 (4.3) | 29 (4.6) | 127 (4.4) |
| Unknown/uncertain | 451 (18.1) | 725 (18.8) | 127 (20.3) | 816 (28.2) |
| Smoking status, n (%) | ||||
| Never | 2221 (89.3) | 3523 (91.3) | 557 (89.0) | 2611 (90.3) |
| Quit smoking for >6 months | 82 (3.3) | 121 (3.1) | 36 (5.8) | 158 (5.5) |
| Current smokers | 183 (7.4) | 214 (5.5) | 33 (5.3) | 124 (4.3) |
| Hypertension, n (%) | ||||
| Normal | 1884 (76.7) | 2972 (77.7) | 479 (77.1) | 2029 (70.5) |
| Hypertension | 572 (23.3) | 852 (22.3) | 142 (22.9) | 849 (29.5) |
| Sleep quality, n (%) | ||||
| Very good | 147 (5.9) | 189 (4.9) | 35 (5.6) | 204 (7.1) |
| Good | 774 (31.1) | 1277 (33.1) | 224 (35.8) | 1000 (34.6) |
| Average | 1179 (47.4) | 1855 (48.1) | 297 (47.4) | 1348 (46.6) |
| Bad | 330 (13.3) | 472 (12.2) | 57 (9.1) | 286 (9.9) |
| Very bad | 56 (2.2) | 65 (1.7) | 13 (2.1) | 55 (1.9) |
Note: Inactive: no engagement in MVPA physical activities. Insufficiently active: engaged in less than 150 min MVPA/week. Weekend warrior: engaged in at least 150 min MVPA/week, but only from one or two sessions weekly. Regularly active: engaged in at least 150 min/week of MVPA from three or more sessions weekly. Abdominal obesity: waist circumference ≥90 cm for men and ≥80 cm for women. BMI conditions was classified by WHO specifically for Asian adults. Hypertension: systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg. The currency used to quantify household income is the HKD.
Abbreviations: BMI, body mass index; HKD, Hong Kong dollar; MVPA, moderate‐to‐vigorous physical activity.
3.2. Association between moderate‐to‐vigorous physical activity patterns and obesity and adiposity
Table 2 presents the associations between MVPA patterns and obesity and adiposity. A significant decrease in obesity risk was observed in logistic regression Models 1–3. In the adjusted models, a hierarchical order of odds ratios was observed, indicating progression from the inactive group to the regularly active group. Subgroup analysis indicated that this association was observed in unadjusted logistic regression models for men and adults aged 40–59 years (Tables S1 and S4).
TABLE 2.
Association between moderate‐to‐vigorous physical activity patterns and obesity.
| Odds ratio (95% CI) | β (95% CI) | |
|---|---|---|
| Physical activity pattern | Obesity (n = 9863) | Body fat percentage (n = 7496) |
| Model 1 | ||
| Inactive | 1 [Reference] | 0 [Reference] |
| Insufficient active | 0.74 (0.66, 0.83) | −1.90 (−2.43, −1.37) |
| Weekend warrior | 0.62 (0.49, 0.77) | −3.76 (−4.60, −2.91) |
| Regularly active | 0.71 (0.63, 0.80) | −3.05 (−3.61, −2.50) |
| Model 2 | ||
| Inactive | 1 [Reference] | 0 [Reference] |
| Insufficient active | 0.87 (0.77, 0.99) | −0.25 (−0.67, 0.18) |
| Weekend warrior | 0.75 (0.60, 0.94) | −1.15 (−1.82, −0.47) |
| Regularly active | 0.73 (0.64, 0.83) | −1.28 (−1.72, −0.84) |
| Model 3 | ||
| Inactive | 1 [Reference] | 0 [Reference] |
| Insufficient active | 0.87 (0.77, 0.98) | −0.33 (−0.76, 0.90) |
| Weekend warrior | 0.75 (0.60, 0.94) | −1.20 (−1.87, −0.53) |
| Regularly active | 0.71 (0.62, 0.81) | −1.42 (−1.86, −0.98) |
Note: Obesity is categorized as having abdominal obesity (waist circumference ≥90 cm for men and ≥80 cm for women) or general obesity (body mass index ≥25 kg/m2). Model 1 was the univariate model in which no covariates were adjusted. Model 2 was adjusted for demographic covariates, including sex, age, education levels and household income levels. Model 3 was additionally adjusted for smoking status, hypertension status and sleep qualities. Odds ratio and beta coefficient in boldface indicate statistical significance.
Abbreviation: CI, confidence interval.
Regarding the association between MVPA patterns and total body fat percentage, the weekend warriors and regularly active groups had significantly lower beta coefficients than the inactive group in the adjusted models. In the subgroup analysis, a hierarchical order of beta coefficients was observed among men and adults aged 17–39 and 40–59 years (Tables S1 and S4).
3.3. Association between moderate‐to‐vigorous physical activity patterns with obesity and adiposity, and distinguishing between the insufficiently active group
Table 3 distinguishes between insufficiently active individuals by frequency of physical activity. Fully adjusted logistic regression models showed that individuals engaged in ≥3 days of MVPA have significantly lower obesity risk than inactive individuals. Similarly, the GLM revealed that insufficiently active individuals who engaged in at least 3 days of physical activity per week had lower body adiposity than inactive individuals. However, all adjusted logistic regression and GLM models showed that insufficiently active individuals who engaged in less than 3 days of MVPA/week did not lower the risk of obesity and body adiposity.
TABLE 3.
Association between moderate‐to‐vigorous physical activity patterns and obesity, distinguishing between the insufficiently active group.
| Odds ratio (95% CI) | β (95% CI) | |
|---|---|---|
| Physical activity pattern | Obesity (n = 9863) | Body fat percentage (n = 7496) |
| Model 1 | ||
| Inactive | 1 [Reference] | 0 [Reference] |
| Insufficiently active, 1 or 2 sessions | 0.72 (0.63, 0.82) | −1.75 (−2.32, −1.17) |
| Insufficient active, ≥3 sessions | 0.77 (0.66, 0.91) | −2.19 (−2.85, −1.52) |
| Weekend warrior | 0.62 (0.49, 0.77) | −3.76 (−4.61, −2.91) |
| Regularly active | 0.71 (0.62, 0.80) | −3.04 (−3.60, −2.48) |
| Model 2 | ||
| Inactive | 1 [Reference] | 0 [Reference] |
| Insufficiently active, 1 or 2 sessions | 0.89 (0.78, 1.02) | −0.02 (−0.48, 0.44) |
| Insufficient active, ≥3 sessions | 0.85 (0.72, 1.00) | −0.62 (−1.15, −0.09) |
| Weekend warrior | 0.75 (0.60, 0.94) | −1.11 (−1.78, −0.44) |
| Regularly active | 0.73 (0.64, 0.83) | −1.25 (−1.69, −0.81) |
| Model 3 | ||
| Inactive | 1 [Reference] | 0 [Reference] |
| Insufficiently active, 1 or 2 sessions | 0.88 (0.77, 1.01) | −0.08 (−0.54, 0.38) |
| Insufficient active, ≥3 sessions | 0.84 (0.71, 0.99) | −0.71 (−1.24, −0.18) |
| Weekend warrior | 0.75 (0.60, 0.94) | −1.16 (−1.83, −0.49) |
| Regularly active | 0.71 (0.62, 0.81) | −1.38 (−1.82, −0.94) |
Note: Obesity is categorized as having abdominal obesity (waist circumference ≥90 cm for men and ≥80 cm for women) or general obesity (body mass index ≥25 kg/m2). Model 1 was the univariate model in which no covariates were adjusted. Model 2 was adjusted for demographic covariates, including sex, age, education levels and household income levels. Model 3 was additionally adjusted for smoking status, hypertension status and sleep qualities. Odds ratio and beta coefficient in boldface indicate statistical significance.
Abbreviation: CI, confidence interval.
3.4. Association between vigorous physical activity patterns, obesity and adiposity
Table 4 provides an analysis of the association between VPA patterns, obesity and body adiposity. The adjusted logistic regression and GLM analyses (Models 2 and 3) showed that engaging in more than three sessions of physical activity per week reduces obesity risk and adiposity, regardless of whether the WHO's physical activity recommendation is met (i.e. being insufficiently active but completing three or more sessions/week or being regularly active). In the subgroup analysis, this association was replicated among men (Table S2).
TABLE 4.
Association between vigorous physical activity patterns and obesity.
| Odds ratio (95% CI) | β (95% CI) | |
|---|---|---|
| Physical activity pattern | Obesity (n = 9863) | Body fat percentage (n = 7496) |
| Model 1 | ||
| Inactive | 1 [Reference] | 0 [Reference] |
| Insufficiently active, 1 or 2 sessions | 0.74 (0.65, 0.85) | −2.40 (−2.89, −1.90) |
| Insufficient active, ≥3 sessions | 0.52 (0.38, 0.71) | −3.46 (−4.43, −2.49) |
| Weekend warrior | 0.73 (0.61, 0.87) | −3.91 (−4.56, −3.26) |
| Regularly active | 0.68 (0.59, 0.79) | −4.83 (−5.35, −4.32) |
| Model 2 | ||
| Inactive | 1 [Reference] | 0 [Reference] |
| Insufficiently active, 1 or 2 sessions | 0.97 (0.84, 1.11) | 0.05 (−0.36, 0.47) |
| Insufficient active, ≥3 sessions | 0.61 (0.44, 0.83) | −0.94 (−1.72, −0.15) |
| Weekend warrior | 0.94 (0.79, 1.13) | −0.40 (−0.95, 0.14) |
| Regularly active | 0.77 (0.67, 0.90) | −1.59 (−2.02, −1.16) |
| Model 3 | ||
| Inactive | 1 [Reference] | 0 [Reference] |
| Insufficiently active, 1 or 2 sessions | 0.95 (0.82, 1.09) | −0.01 (−0.40, 0.43) |
| Insufficient active, ≥3 sessions | 0.58 (0.42, 0.79) | −1.14 (−1.91, −0.36) |
| Weekend warrior | 0.92 (0.77, 1.11) | −0.48 (−1.02, 0.06) |
| Regularly active | 0.76 (0.65, 0.88) | −1.69 (−2.11, −1.26) |
Note: Obesity is categorized as having abdominal obesity (waist circumference ≥90 cm for men and ≥80 cm for women) or general obesity (body mass index ≥25 kg/m2). Model 1 was the univariate model in which no covariates were adjusted. Model 2 was adjusted for demographic covariates, including sex, age, education levels and household income levels. Model 3 was additionally adjusted for smoking status, hypertension status and sleep qualities. Odds ratio and beta coefficient in boldface indicate statistical significance.
Abbreviation: CI, confidence interval.
Furthermore, the regular active pattern was significantly associated with a lower body fat percentage than the inactive pattern. No significant association was observed between obesity and body fat percentage in insufficiently active and weekend warriors. In addition, subgroup analysis revealed that weekend warriors were significantly associated with a lower body fat percentage than the inactive group among men and adults aged 40–59 years (Tables S2 and S5).
3.5. Association between weekly duration of moderate‐to‐vigorous physical activity, obesity and adiposity
Table 5 shows the relationship between weekly MVPA durations, obesity and body adiposity. The fully adjusted logistic regression models and GLM indicated that engaging in the minimum recommended MVPA duration (150 min/week) significantly reduced the obesity risk and body fat percentage. Furthermore, this association was observed only in the GLM subgroup analysis among men and adults aged 40–59 years (Tables S3 and S6).
TABLE 5.
Association between moderate‐to‐vigorous physical activity duration and obesity.
| Odds ratio (95% CI) | β (95% CI) | |
|---|---|---|
| Physical activity pattern | Obesity (n = 9863) | Body fat percentage (n = 7496) |
| Model 1 | ||
| None | 1 [Reference] | 0 [Reference] |
| 10–74.9 min | 0.74 (0.64, 0.84) | −1.64 (−2.22, −1.05) |
| 75–149.9 min | 0.74 (0.64, 0.86) | −2.30 (−2.94, −1.66) |
| 150–299.9 min | 0.65 (0.56, 0.76) | −2.89 (−3.51, −2.27) |
| ≥300 min | 0.73 (0.63, 0.84) | −3.44 (−4.05, −2.82) |
| Model 2 | ||
| None | 1 [Reference] | 0 [Reference] |
| 10–74.9 min | 0.89 (0.77, 1.02) | −0.08 (−0.55, 0.38) |
| 75–149.9 min | 0.86 (0.74, 1.00) | −0.46 (−0.97, 0.06) |
| 150–299.9 min | 0.72 (0.62, 0.84) | −1.01 (−1.50, −0.51) |
| ≥300 min | 0.74 (0.64, 0.86) | −1.44 (−1.93, −0.95) |
| Model 3 | ||
| None | 1 [Reference] | 0 [Reference] |
| 10–74.9 min | 0.88 (0.77, 1.02) | −0.13 (−0.59, 0.34) |
| 75–149.9 min | 0.84 (0.72, 0.99) | −0.58 (−1.09, −0.07) |
| 150–299.9 min | 0.70 (0.60, 0.81) | −1.15 (−1.64, −0.66) |
| ≥300 min | 0.73 (0.63, 0.85) | −1.53 (−2.02, −1.04) |
Note: Obesity is categorized as having abdominal obesity (waist circumference ≥90 cm for men and ≥80 cm for women) or general obesity (body mass index ≥25 kg/m2). Model 1 was the univariate model in which no covariates were adjusted. Model 2 was adjusted for demographic covariates, including sex, age, education levels and household income levels. Model 3 was additionally adjusted for smoking status, hypertension status and sleep qualities. Odds ratio and beta coefficient in boldface indicate statistical significance.
Abbreviation: CI, confidence interval.
4. DISCUSSION
Our study highlights several important findings. First, we discovered that the weekend warrior activity pattern significantly lowers the risk of abdominal and general obesity, as well as body fat levels. This finding suggests that even concentrating physical activity into 1 or 2 days/week can lower obesity risk and body fat. Second, we observed that even when the total physical activity falls short of the recommended 150 min/week, engaging in at least three weekly MVPA sessions still helps reduce abdominal and general obesity, along with total body adiposity. Therefore, frequency of physical activity is crucial in managing obesity, particularly for insufficiently active individuals. Lastly, engaging in half of the recommended physical activity volume (75–149.9 min) remained associated with significant reductions in obesity and body fat percentage.
Our hypothesis that weekend warriors and regularly active individuals would show similar obesity reductions because of their equal weekly energy expenditure was supported by our findings. Two cross‐sectional studies discovered that engaging in 150 min of MVPA 1 or 2 days/week had no significant association with reducing abdominal obesity. 4 , 5 These findings align with those of our study, which found no significant reduction in the risk of abdominal obesity in weekend warrior activity patterns. However, unlike previous studies, we used a combination of BMI and waist circumference to identify obesity, as recommended by recent guidelines for a more accurate assessment. 6 This dual approach revealed that weekend warrior patterns may benefit individuals with combined abdominal and general obesity. Individuals with higher waist circumference and BMI have an increased likelihood of developing type 2 diabetes 16 , 17 and cardiovascular diseases, 16 , 18 facing a higher risk of mortality. 19 , 20 Engaging in weekend warrior activity can positively affect high‐risk populations. BMI and waist circumference are well‐recognized markers of obesity; however, they do not directly reflect body adiposity. Therefore, we included body fat measurements to better understand the effects of physical activity patterns on obesity. Our results showed an association between weekend warrior activity patterns and lower total body fatness.
A major barrier to regular physical activity is a lack of time. 21 The weekend warrior pattern can help lower the frequency of commitment, although it may still be challenging for individuals who struggle to find 150 min for MVPA throughout the week. Our secondary analysis investigated whether frequency and duration of physical activity matter in mitigating obesity risk. We adopted the analysis by O'Donovan et al., 22 which categorized the insufficiently active group into two segments based on frequency: MVPA for one or two sessions/week and MVPA for more than three sessions/week. Currently, the WHO suggests that ‘some physical activity is better than none for those who do not currently meet these recommendations’. 1 Our findings indicated that individuals not currently meeting these recommendations could benefit from distributing their physical activity over more days to maximize benefits, reduce the risk of abdominal and general obesity, and reduce adiposity.
Our findings revealed that more than three weekly VPA sessions, regardless of adherence to the prevailing physical activity guidelines, significantly reduced obesity and adiposity risk. Conversely, vigorous‐intensity weekend warrior activity alone was insufficient to achieve a positive effect on obesity, emphasizing that frequency plays a key role in managing obesity and adiposity through VPA.
Our study also confirmed the WHO's recommendation 1 that achieving ≥150 min of MVPA weekly can significantly reduce obesity risk. We further observed a dose–response relationship, where increased weekly physical activity progressively lowered body fat percentage. The American College of Sports Medicine suggests 200–300 min of moderate‐intensity activity for sustained weight loss 23 ; however, understanding the minimum effective dose is important for time‐constrained individuals.
Our study has several strengths. First, we used Asian‐specific waist circumference and BMI standards to identify various obesity phenotypes, providing a more comprehensive understanding of the relationship between physical activity and obesity. Second, we utilized a Gulick tape for more accurate abdominal obesity measurements, improving on previous studies. 4 , 5 Third, the use of RPE scales and clear examples of moderate‐ and vigorous‐intensity activities probably improved the reliability of our findings. Lastly, to our knowledge, this study is the first to examine the impact of weekend warrior activity on body fat, adding a new dimension to our understanding of the role of physical activity in obesity management.
Our study had some limitations. First, the cross‐sectional study design limits the ability to determine causality or long‐term effects. Future randomized controlled trials or cohort studies could address this limitation and investigate potential risks, such as overuse injuries. Second, physical activity was self‐reported, which may introduce bias, and future studies should include objective measures like accelerometers. Third, our questionnaires focus on MVPA and VPA, leaving out specific inquiries about moderate‐intensity activity patterns. Lastly, our survey followed the 2010 WHO guidelines, 24 which only counted bouts of physical activity lasting ≥10 min, whereas the current guidelines allow for any activity duration.
In conclusion, our study showed that weekend warrior activity patterns, more than three MVPA sessions per week but below the recommended volume and even half the recommended volume, can reduce the risk of obesity. These findings offer valuable insights into the relationship between physical activity patterns and obesity, informing the public, health care professionals and policymakers about effective strategies to combat obesity.
AUTHOR CONTRIBUTIONS
SS‐cH and EC‐yC contributed to the conception, design, statistical analysis, and manuscript writing. SS‐cH and BP‐SC estimated the sample size. SS‐cH, JKWC, JH‐pW, BP‐SC and SW‐SW performed the data collection and management.
CONFLICT OF INTEREST STATEMENT
The authors have no conflicts of interest to declare.
PEER REVIEW
The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/dom.16017.
Supporting information
Data S1: Supporting Information.
ACKNOWLEDGEMENTS
The authors express their gratitude for the generous funding support and approval to use the database provided by the Leisure and Cultural Services Department of the Government of Hong Kong. The authors also thank the RGC Postdoctoral Fellowship Scheme (PDFS2324‐4H01) for supporting this study. Appreciation is extended to the fitness assessors from the Physical Fitness Association of Hong Kong, China, whose professionalism contributed to the study. Furthermore, the authors would like to thank all Hong Kong citizens who volunteered their time and efforts to participate in the survey. The Leisure and Cultural Services Department under the Government of the Hong Kong Special Administrative Region funded the Hong Kong Territory‐wide Physical Fitness Survey in 2011 and 2021. SS‐cH served as the principal investigator for both grants.
Hui SS, Chin EC, Chan JKW, Chan BP‐S, Wan JH, Wong SW‐S. Association of ‘weekend warrior’ and other leisure time physical activity patterns with obesity and adiposity: A cross‐sectional study. Diabetes Obes Metab. 2025;27(2):482‐489. doi: 10.1111/dom.16017
DATA AVAILABILITY STATEMENT
The data are available from the corresponding author upon reasonable request and approval from the Leisure and Cultural Services Department of the Government of Hong Kong.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1: Supporting Information.
Data Availability Statement
The data are available from the corresponding author upon reasonable request and approval from the Leisure and Cultural Services Department of the Government of Hong Kong.