To examine whether the “Short QUestionnaire to ASsess Health-enhancing physical activity” (SQUASH) and the “Injuries and Physical Activity in the Netherlands” questionnaire (“Ongevallen en Bewegen in Nederland,” OBiN) were valid in assessing adherence to physical activity (PA) guidelines.
Study Design and Setting
Participants (N = 187) aged 20–69 years were categorized as “inactive,” “semiactive,” or “norm-active” according to the Dutch PA, the American College of Sports Medicine (ACSM), and the combined guideline (adhering to either or both of two other guidelines) by the questionnaires and a combined heart rate monitor and accelerometer (Actiheart). Percentage of exact agreement and maximum disagreement (difference of two categories) for the categorization between questionnaires and Actiheart was calculated.
Results
The SQUASH had a significant higher agreement than the OBiN for the Dutch PA (SQUASH: 78%, OBiN: 46%; P < 0.01) and combined guideline (SQUASH: 84%, OBiN: 55%; P < 0.01). Both questionnaires had a low agreement regarding the ACSM guideline (SQUASH: 37%, OBiN: 34%; P = 0.45). The SQUASH had a significant higher maximum disagreement than the OBiN for this guideline (SQUASH: 19.8%, OBiN 8%; P < 0.01).
Conclusion
The SQUASH was a more valid measure than the OBiN for categorizing adults according to the Dutch PA and the combined guideline. Both questionnaires failed to correctly categorize adults according to the ACSM guideline.
Introduction
What is new?
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The “Short QUestionnaire to ASsess Health-enhancing physical activity” (SQUASH) was a more valid measure than the “Injuries and Physical Activity in the Netherlands” questionnaire (“Ongevallen en Bewegen in Nederland,” OBiN) in categorizing Dutch adults according to the Dutch physical activity (PA) guideline and the combined guideline (combination of adhering to either or both of the Dutch PA guideline and the American College of Sports Medicine [ACSM] guideline for cardiorespiratory fitness). Both the SQUASH and the OBiN questionnaire failed to correctly categorize adults according to the ACSM guideline.
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PA questionnaires are often used to measure PA behavior. In the Netherlands, the SQUASH and OBiN questionnaire are often used but have not been validated with the same objective measurement before. This study gains insight in the ability of these questionnaires to measure adherence to PA guidelines.
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PA may be ultimately measured with objective instruments, but until then, it is of great importance that future research will aim to obtain more insight into the validity of both objective and subjective instruments.
It is well established that physically active people have higher levels of health-related fitness, lower rates of various chronic diseases, and a lower risk profile for developing several disabling medical conditions [1], [2]. Physical activity (PA) guidelines have been developed to help populations to achieve these health benefits [1].
In the Netherlands, generally three PA guidelines are used.
1.
The Dutch PA guideline, recommending 30 minutes or more of at least moderate intense PA for a minimum of 5 days per week [3]
2.
The 1998 American College of Sports Medicine (ACSM) guideline—also known as the guideline for cardiorespiratory fitness—recommending 20 minutes or more of vigorous PA for at least 3 days per week [4]
3.
The combined guideline, which means adhering to either or both of the above two described guidelines [5].
These guidelines are similar to those in, for example, the United States [1], but they differ with respect to cutoff values of moderate and vigorous intense PA. In the Netherlands, cutoff values of respectively 4.0 and 6.5 METs are used, whereas internationally, cutoff values of 3.0 and 5.0 are more common. This results in, for example, walking being excluded from the guidelines in the Netherlands as opposed to other countries.
In the Netherlands, two questionnaires are used to monitor adherence to these guidelines in country-wide representative surveys on a yearly basis: the “Short QUestionnaire to ASsess Health-enhancing physical activity” (SQUASH; Appendix 1 [see Appendix 1 on the journal's Web site at www.elsevier.com]) [6] and the “Injuries and Physical Activity in the Netherlands” questionnaire (“Ongevallen en Bewegen in Nederland,” OBiN; Appendix 2 [see Appendix 2 on the journal's Web site at www.elsevier.com]) [7]. Although both questionnaires provide the opportunity to measure adherence to guidelines, they differ substantially in reference period, type of questions, and operationalization of the guidelines. The SQUASH has been designed to measure the habitual activity level in general [6], whereas the OBiN questionnaire has been specifically designed to measure habitual activity level in terms of adherence to the three guidelines mentioned above [7]. Both the SQUASH and OBiN questionnaire have been validated in the past, but never simultaneously. Furthermore, different reference methods (i.e., Computer Science and Applications Activity Monitor and extensive PA questionnaire) and outcome measures (i.e., PA scores and adherence to guidelines) have been used [6], [7].
There is consensus that for the purpose of validating questionnaires, an objective measure (e.g., doubly labeled water, accelerometer, or heart rate monitor) is preferred over a subjective measure (e.g., direct observation, diary, or questionnaire) [8]. Recently, a combined accelerometer with a heart rate monitor (Actiheart; Cambridge Neurotechnology, Cambridge, UK) has been developed, which provides a more valid measure of PA levels than using an accelerometer or heart rate meter separately [9]. This makes the Actiheart a good objective measure to validate questionnaires.
The aim of the present study was to validate results of the SQUASH and OBiN questionnaire against the Actiheart within an adult population by using adherence to the Dutch PA guideline, ACSM guideline, and combined guideline as outcome measures.
Section snippets
Study population
Participants were included if they were aged between 20 and 69 years and were not suffering from a disorder that would influence heart rate measurements. Also, participants had to be able to walk for 10 minutes without aid. Participants were recruited from two sources: (1) a volunteer database from the Julius Center for Health Sciences and (2) advertisement posters, which were placed at the Utrecht University Medical Center. We used the large volunteer database because it included participants
Characteristics of the population
Table 1 shows the characteristics of the study population. The population consisted of 27 men and 160 women aged 57 ± 11 years (men: 51 ± 10 and women: 58 ± 11 years). Approximately three-quarters of participants were aged 55 years and older. About half of the study population had a high educational level (Table 1).
Adherence to the guidelines
Fig. 1 shows the proportion of the study population categorized as “inactive,” “semiactive,” or “norm-active” according to the three guidelines under study. The SQUASH showed patterns
Discussion
The present study showed in a population of 187 adults aged 20–69 years that the SQUASH had a higher exact agreement with the Actiheart than the OBiN questionnaire to categorize participants according to the Dutch PA guideline and the combined guideline. Both questionnaires had a relatively low but comparable exact agreement with the Actiheart regarding the ACSM guideline.
In the present study, we used the Actiheart to validate the two questionnaires, which is a more accurate method than using
Conclusion
The SQUASH was a more valid measure in categorizing adults according to the Dutch PA guideline and the combined guideline than the OBiN questionnaire. Both the SQUASH and the OBiN questionnaire failed to correctly categorize adults according to the ACSM guideline.
Acknowledgments
The study was performed in cooperation with the Julius Center for Health Sciences, Primary Care University Medical Center, Utrecht, the Netherlands, and Cambridge Neurotechnology, Cambridge, UK. The Julius Center measured anthropometrics and physical activity. Cambridge Neurotechnology cleaned the Actiheart data.
The fieldwork was coordinated by a trained research coordinator of the Julius Center for Health Sciences and supervised by a principal researcher from the National Institute for Public
American College of Sports Medicine Position Stand
The recommended quantity and quality of exercise for developing and maintaining cardiorespiratory and muscular fitness, and flexibility in healthy adults
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Meeting the 60-min physical activity guideline: effect of operationalization
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Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity
It is unclear to what extent mental health and negative life events (NLEs) contribute to weight change in patients with overweight. This study aimed to evaluate the association of anxiety, depression, NLEs and quality of life (QoL) with weight change over ten years in middle-aged individuals with overweight.
Population-based cohort study of 2889 middle-aged men and women with a body mass index ≥27 kg/m2. Relative weight change over ten years was defined as weight loss (≤− 5 %), stable weight (between >− 5 % and <5 %) or weight gain (≥5 %). At baseline, participants reported anxiety symptoms, depressive symptoms, recent (last year) and distant (lifetime) NLEs, and a mental component summary of QoL. With multinomial logistic regression adjusting for potential confounding, we examined the association of mental health and NLEs with weight change after a median (25th, 75th percentiles) follow-up of 9.7 (9.0–10.5) years.
In 51 % participants weight was stable, 33 % participants lost weight and 17 % gained weight. Mild (odds ratio 1.36; 95 % confidence interval 1.05–1.75), and moderate to very severe depressive symptoms (1.43; 0.97–2.12) and four or more distant NLEs (1.35; 1.10–1.67) were associated with weight gain. Anxiety symptoms, the mental component summary of QoL were not associated with either weight gain or weight loss.
Due to the observational design residual confounding cannot be excluded.
Our study suggests that depressive symptoms or having experienced distant NLEs are associated with weight gain over time in middle-aged individuals with overweight. These subgroups might benefit from proactive attention from their health care providers.
Patients with non-muscle invasive bladder cancer (NMIBC) are at a high risk of tumor recurrence. It has not been previously investigated if adherence to cancer prevention recommendations lowers the risk of recurrence.
We examined whether the standardized lifestyle score measuring adherence to the 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations was associated with the risk of recurrence and progression among patients with NMIBC.
The study population included patients diagnosed with primary NMIBC between 2014 and 2017 from the prospective cohort UroLife. Lifestyle was assessed at baseline (n = 979; reflecting the prediagnosis period) and 3-mo postdiagnosis (n = 885). The standardized 2018 WCRF/AICR score was constructed based on recommendations for body weight, physical activity, diet, and alcohol intake. We computed multivariable-adjusted HRs and 95% CIs using Cox proportional hazard regression models.
During a median follow-up time of 3.7 y, 320 patients developed ≥1 recurrence(s) and 49 experienced progression. Patients in the highest compared with the lowest tertile of postdiagnosis WCRF/AICR scores had a lower risk of first bladder cancer recurrence (HR: 0.74; 95% CI: 0.56, 0.98). No associations were observed for multiple recurrences (HR: 0.90; 95% CI: 0.70, 1.15) or for the baseline score with either first (HR: 1.07; 95% CI: 0.82, 1.40) or multiple recurrences (HR: 1.04; 95% CI: 0.82, 1.31). Improving lifestyle after diagnosis (per 1-point increase) was not significantly associated with the risk of first or multiple recurrence(s) (HR: 0.87; 95% CI: 0.74, 1.02; HR: 0.93; 95% CI: 0.80, 1.08, respectively). No associations were observed for bladder cancer progression, but the power was limited.
Better adherence to the WCRF/AICR cancer prevention recommendations 3 mo after NMIBC diagnosis, but not before diagnosis, is associated with a decreased risk of first bladder cancer recurrence. More studies evaluating postdiagnosis lifestyles are needed to provide solid support for lifestyle recommendations for cancer survivors.
2021, Nutrition, Metabolism and Cardiovascular Diseases
The accumulation of fat increases the formation of lipid peroxides, which are partly scavenged by alpha-tocopherol (α-TOH). Here, we aimed to investigate the associations between different measures of (abdominal) fat and levels of urinary α-TOH metabolites in middle-aged individuals.
In this cross-sectional analysis in the Netherlands Epidemiology of Obesity study (N = 511, 53% women; mean [SD] age of 55 [6.1] years), serum α-TOH and α-TOH metabolites from 24-h urine were measured as alpha-tocopheronolactone hydroquinone (α-TLHQ, oxidized) and alpha-carboxymethyl-hydroxychroman (α-CEHC, enzymatically converted) using liquid-chromatography-tandem mass spectrometry. Body mass index and total body fat were measured, and abdominal subcutaneous and visceral adipose tissue (aSAT and VAT) were assessed using magnetic resonance imaging. Using multivariable-adjusted linear regression analyses, we analysed the associations of BMI, TBF, aSAT and VAT with levels of urinary α-TOH metabolites, adjusted for confounders. We observed no evidence for associations between body fat measures and serum α-TOH. Higher BMI and TBF were associated with lower urinary levels of TLHQ (0.95 [95%CI: 0.90, 1.00] and 0.94 [0.88, 1.01] times per SD, respectively) and with lower TLHQ relative to CEHC (0.93 [0.90, 0.98] and 0.93 [0.87, 0.98] times per SD, respectively). We observed similar associations for VAT (TLHQ: 0.94 [0.89, 0.99] times per SD), but not for aSAT.
Opposite to our research hypothesis, higher abdominal adiposity was moderately associated with lower levels of oxidized α-TOH metabolites, which might reflect lower vitamin E antioxidative activity in individuals with higher abdominal fat instead.
An unhealthy lifestyle is associated with the risk of colorectal cancer (CRC), but it is unclear whether overall lifestyle after a CRC diagnosis is associated with risks of recurrence and mortality.
To examine associations between postdiagnosis lifestyle and changes in lifestyle after a CRC diagnosis with risks of CRC recurrence and all-cause mortality.
The study population included 1425 newly diagnosed, stage I–III CRC patients from 2 prospective cohort studies enrolled between 2010 and 2016. Lifestyle, including BMI, physical activity, diet, and alcohol intake, was assessed at diagnosis and at 6 months postdiagnosis. We assigned lifestyle scores based on concordance with 2 sets of cancer prevention guidelines—from the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) and the American Cancer Society (ACS)—and national disease prevention guidelines. Higher scores indicate healthier lifestyles. We computed adjusted HRs and 95% CIs using Cox regression.
We observed 164 recurrences during a 2.8-year median follow-up and 171 deaths during a 4.4-year median follow-up. No associations were observed for CRC recurrence. A lifestyle more consistent with the ACS recommendations was associated with a lower all-cause mortality risk (HR per +1 SD, 0.85; 95% CI: 0.73–0.995). The same tendency was observed for higher WCRF/AICR (HR, 0.92; 95% CI: 0.78–1.08) and national (HR, 0.90; 95% CI: 0.77–1.05) lifestyle scores, although these associations were statistically nonsignificant. Generally, no statistically significant associations were observed for BMI, physical activity, diet, or alcohol. Improving one’s lifestyle after diagnosis (+1 SD) was associated with a lower all-cause mortality risk for the ACS (HR, 0.80; 95% CI: 0.67–0.96) and national (HR, 0.84; 95% CI: 0.70–0.999) scores, yet was statistically nonsignificant for the WCRF/AICR score (HR, 0.94; 95% CI: 0.78–1.13).
A healthy lifestyle after CRC diagnosis and improvements therein were not associated with the risk of CRC recurrence, but were associated with a decreased all-cause mortality risk.
2020, Archives of Physical Medicine and Rehabilitation
Citation Excerpt :
The patient global assessment evaluated patient-rated general health.13 The Short Questionnaire to Assess Health-Enhancing Physical Activity collected data on habitual physical activity during the previous month,14,15 of which total minutes of physical activity were calculated. QoL was measured with the Rand 36-item Health Survey and the mental component score and physical component score were calculated.16
To assess the efficacy of a 12-week aquatic cycling training program for improving knee pain and physical functioning in patients with knee osteoarthritis (OA).
OA outpatient clinic of the Maastricht University Medical Center+.
Patients (N=111, 50-70y) with unilateral mild-to-moderate knee OA.
Participants (aquatic cycling [AC] group, n=55) received AC sessions of 45 min each 2 times per week. Each session combined upright seated cycling with out-of-saddle positions and exercises for the upper and lower body. The usual care (UC) group (n=47) continued with UC and was offered 12 AC sessions in a local swimming pool after their trial participation.
The Knee Injury and Osteoarthritis Outcome Score (KOOS) on knee pain and physical function was assessed at baseline, postintervention, and at 24-wk follow-up. Multilevel (mixed regression) analysis examined the effects.
Average attendance rate for the AC sessions was 80%. Statistically significant differences at postintervention and follow-up were found for knee pain in mean ± SD (UC pretest, 57.89±15.26; posttest, 55.90±18.04; follow-up, 57.24±19.16; and AC pretest, 56.96±12.96; posttest, 63.55±15.33; follow-up, 64.35±17.26; estimate, 8.16; SE, 3.27; 95% confidence interval [CI], 1.67-14.64; effect size [ES], 0.50) and physical functioning (UC pretest, 66.32±16.28; posttest, 66.80±19.04; follow-up, 65.42±17.98; and AC pretest, 61.89±17.151; posttest, 70.14±17.52; follow-up, 69.00±16.84; estimate, 7.16; SE, 3.19; 95% CI, 0.83-13.49; ES, 0.43) in favor of the aquatic group.
The results suggest that a 12-week AC training program improves self-reported knee pain and physical functioning in patients with mild-to-moderate knee OA compared to UC.
In our study, active cancer was defined as currently having a neoplasm or cancer and not having been “medically cured”. Additionally, participants reported the frequency, duration, and intensity of their physical activity during leisure time on the Short Questionnaire to Assess Health-enhancing physical activity (SQUASH), which was expressed in metabolic equivalent of task (MET) hours per week [11]. The participants were asked to bring all medication they were using to the study visit, including oral contraceptives and hormonal replacement therapy.
The adipocyte-derived hormone leptin has been associated with altered blood coagulation in in vitro studies. However, it is unclear whether this association is relevant in vivo and to what extent this association is influenced by total body fat. Therefore, we aimed to examine the association between serum leptin and blood coagulation while taking total body fat into account in a population-based cohort study.
We performed a cross-sectional analysis with baseline measurements of 5797 participants of the Netherlands Epidemiology of Obesity (NEO) study, a population-based cohort of middle-aged men and women. We examined associations between serum leptin concentration and coagulation factor concentrations and parameters of platelet activation in linear regression analyses. All analyses were adjusted for multiple covariates, including total body fat.
In multivariable adjusted analyses a 1 μg/L higher serum leptin concentration was associated with a 0.22 IU/dL (95% CI: 0.11, 0.32) higher FVIII concentration and a 0.20 IU/dL (95% CI: 0.14, 0.27) higher FIX concentration (3.5 IU/dL FVIII and 3.2 IU/dL FIX per SD leptin). Serum leptin concentration was not associated with FXI, fibrinogen, platelet count, mean platelet volume and platelet distribution width in multivariable adjusted analyses.
This study showed that serum leptin concentration was associated with higher concentrations of FVIII and FIX in an observational study, which could be clinically relevant.