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Relationship between Meeting Physical Activity Guideline Parameters and Body Mass Index (BMI) in Adults

Peter D. Hart
Journal of Physical Activity Research. 2021, 6(2), 130-134. DOI: 10.12691/jpar-6-2-11
Received September 02, 2021; Revised October 05, 2021; Accepted October 13, 2021

Abstract

Background: Physical activity (PA) and risk of obesity are inversely related in adult populations. However, the extent to which meeting different PA guidelines influence body mass index (BMI) is less known. The aim of this research was to examine how different PA guideline parameters affect BMI in adults. Methods: The Montana Behavioral Risk Factor Surveillance System (BRFSS, 2019) was used for this study. Four different PA guideline variables were used and included 1) 2-level aerobic PA (APA) (met APA or did not meet APA), 2) 2-level muscle strengthening activity (MSA) (met MSA or did not meet MSA), 3) 4-level PA (met both APA and MSA, met APA only, met MSA only, or met neither), and 4) 3-level APA categories (active, insufficiently active, or inactive). BMI was calculated from self-reported height and weight (kg/m2). Multiple linear regression was used to examine the effect of each PA guideline parameter on BMI while controlling for sociodemographic variables. Results: Findings showed that meeting the 2-level APA (slope (b) = -0.74 kg/m2, p < .0001) or the 2-level MSA (b = -0.75 kg/m2, p < .0001) guideline was associated with lower mean BMI. In the 4-level PA model, as compared to meeting neither guideline, meeting APA only (b = -0.58 kg/m2, p = .0119) or meeting both APA and MSA (b = -1.32 kg/m2, p < .0001) was associated with lower mean BMI. Meeting MSA only did not show significantly (p = .1748) different BMI from those meeting neither guideline. In the 3-level APA model, as compared to those categorized as inactive, those categorized as active (b = -0.91 kg/m2, p < .0001) had lower mean BMI. Those categorized as insufficiently active did not have significantly (p = .1748) different BMI from those categorized as inactive. Furthermore, the 4-level PA guidelines × sex interaction was significant (p = .030) and indicated lower mean BMI for females meeting either MSA only (b = -1.05 kg/m2, p = .0215), APA only (b = -1.14 kg/m2, p = .0014), or both APA and MSA (b = -1.84 kg/m2, p < .0001) guideline (p for trend < .0001). Whereas for males, only meeting both APA and MSA was associated with lower mean BMI (b = -0.77 kg/m2, p = .0077). Conclusion: This study found that meeting either APA or MSA guideline is associated with lower BMI in adults. However, sex-specific analyses indicate that this is true for females only and in dose-response fashion. Lower BMI in males is only associated with meeting both APA and MSA guidelines. Health promotion specialists concerned with obesity should understand the influence that each PA guideline has on relative body weight. Physical activity programming should promote both APA and MSA among adults in Montana.

1. Introduction

Obesity is linked to several different health problems in adults and in response the United States (U.S.) has set a goal for reducing its prevalence from approximately 38% (2016) to 36% by year 2030 1. One behavioral approach for reducing obesity is increasing physical activity (PA). Many cross-sectional studies have reported an inverse PA and obesity relationship 2, 3, 4. Moreover, interventions using PA as a component show weight-related improvements in obese populations 5, 6. Body mass index (BMI) is a common measure used to classify obesity, especially in large populations 7. BMI is computed as body mass in kilograms over height in meters squared (BMI = kg/m2). Studies have also reported inverse associations between PA and BMI 8, 9, 10.

The 2018 Physical Activity Guidelines for Americans state that adults do 150+ minutes of moderate-intensity or 75+ minutes of vigorous-intensity, or an equivalent combination of moderate-to-vigorous-intensity PA (MVPA) each week 11. These PA guidelines are recommended for their health advantages, which include body weight benefits. Some studies have shown an inverse relationship between meeting PA guidelines and obesity 12, 13, 14. However, less is known about the relationship between meeting PA guidelines and BMI in adults. Additionally, no studies have examined the extent to which meeting different PA guidelines influences BMI in adults. Therefore, the purpose of this study was to examine how different PA guideline parameters relate to BMI in an adult population.

2. Materials & Methods

Data for this study cam from the Behavioral Risk Factor Surveillance System (BRFSS, 2019). BRFSS methodological details can be found elsewhere 12, 13. The BRFSS is a state-based annual telephone survey aimed at collecting data about health factors related to the leading causes of premature morbidity and mortality. The BRFSS samples noninstitutionalized U.S. adults 18+ years of age. The Montana BRFSS data were extracted from the larger dataset for this study and BMI was restricted to < 40 kg/m2.

Four different PA guideline variables were used in this study. A two-level aerobic PA (APA) variable was constructed and participants were classified as either those that “met APA” or “did not meet APA” guidelines. A two-level muscle strengthening activity (MSA) variable was constructed and participants were classified as either those that “met MSA” or “did not meet MSA” guidelines. A four-level PA variable was constructed and participants were classified as either those that “met both APA and MSA”, “met APA only”, “met MSA only”, or “met neither” guideline. Finally, a three-level APA categories variable was constructed and participants were classified as either those that are “active”, “insufficiently active”, or “inactive”. Meeting APA was determined from a series of questions asking participants about their PA and exercise during the previous month. After reporting the types of activities, the usual frequency, and usual duration, a total minutes of PA per week was computed for each respondent. Those reporting 150+ minutes of total MVPA per week were considered “active” and “met APA” guidelines. Those reporting some PA but less than 150 minutes of total MVPA per week were considered “insufficiently active” and “did not meet APA” guidelines. Those reporting no PA were considered “inactive” and “did not meet APA” guidelines.

Meeting MSA was determined from a series of questions asking participants about their muscle strengthening PA and exercise during the previous month. Participants reporting 2+ days per week of MSA were considered those that “met MSA” guidelines and participants reporting less than 2 days per week were considered those that “did not meet MSA” guidelines. BMI was calculated from self-reported height and weight (kg/m2). Study covariates included sex, age, race/ethnicity, income, education, and rural/urban status.

Statistical analyses included means, standard errors (SEs) and 95% confidence intervals (CIs) for BMI across APA and MSA parameter status. Test for difference in means were performed using regression analysis t statistics. Multiple linear regression was used to estimate the mean BMI difference (unstandardized slope, b) for each PA guideline parameter in separate models. All multiple regression models were controlled for sex, age, race/ethnicity, income, education, and rural/urban status. Analyses were weighted to produce generalizations representative of noninstitutionalized adults in Montana. SAS version 9.4 and SPSS version 27 were used for all analyses 14, 15, 16, 17.

3. Results

Overall, a total of N = 5,772 participants (BMI < 40 kg/m2) had complete BMI (Mean = 26.95, 95% SE = 0.076) data and pairwise deletion was used for all other analyses. Table 1 contains mean BMI comparisons by APA guideline status overall and across sociodemographic characteristics. Montana adults meeting APA guidelines (Mean = 26.66, SE = 0.09) had significantly (p < .0001) lower BMI than those not meeting APA guidelines (Mean = 27.43, SE = 0.14). Additionally, females meeting APA guidelines (Mean = 26.03, SE = 0.14) had significantly (p < .0001) lower BMI than those not meeting APA guidelines (Mean = 27.25, SE = 0.21). Whereas no APA status differences were seen for males. Race/ethnicity groups saw little APA status difference, with exception for the White race group, with those meeting APA guidelines (Mean = 26.62, SE = 0.10) having significantly (p < .0001) lower BMI than those not meeting APA guidelines (Mean = 27.33, SE = 0.15).

Table 2 contains mean BMI comparisons by MSA guideline status overall and across sociodemographic characteristics. Montana adults meeting MSA guidelines (Mean = 26.41, SE = 0.12) had significantly (p < .0001) lower BMI than those not meeting MSA guidelines (Mean = 27.29, SE = 0.10). Additionally, females meeting MSA guidelines (Mean = 25.79, SE = 0.18) had significantly (p < .0001) lower BMI than those not meeting MSA guidelines (Mean = 26.96, SE = 0.16). Similarly, males meeting MSA guidelines (Mean = 26.92, SE = 0.15) had significantly (p = .0008) lower BMI than those not meeting MSA guidelines (Mean = 27.60, SE = 0.13). Race/ethnicity groups once again saw little difference for MSA status, with exception again for the White race group, with those meeting MSA guidelines (Mean = 26.31, SE = 0.12) having significantly (p < .0001) lower BMI than those not meeting MSA guidelines (Mean = 27.24, SE = 0.11).

Table 3 contains results for the four models of BMI regressed on the different PA guideline parameters. Findings showed that meeting the 2-level APA (slope (b) = -0.74 kg/m2, p < .0001) or the 2-level MSA (b = -0.75 kg/m2, p < .0001) guideline was associated with lower mean BMI. In the 4-level PA model, as compared to meeting neither guideline, meeting APA only (b = -0.58 kg/m2, p = .0119) or meeting both APA and MSA (b = -1.32 kg/m2, p < .0001) was associated with lower mean BMI. Meeting MSA only did not show significantly (p = .1748) different mean BMI from those meeting neither guideline. In the 3-level APA model, as compared to those categorized as inactive, those categorized as active (b = -0.91 kg/m2, p < .0001) had lower mean BMI. Those categorized as insufficiently active did not have significantly (p = .1748) different mean BMI from those categorized as inactive.

  • Figure 1. Mean BMI across 4-level PA guidelines status by sex in Montana adults, 2019 (Note. N = 4,596. Body mass index (BMI) computed from self-reported height and weight (kg/m2). Adjusted unstandardized slopes (bs) are by sex and controlled for age, race/ethnicity, income, education, and rural/urban status. Slope values in bold are significantly (p < .05) different from their sex-specific reference (ref). Population restricted to BMI < 40 kg/m2.)

Figure 1 displays mean BMI across 4-level PA guidelines status by sex. This graph shows visually the apparent PA guidelines status × sex interaction (p = .030) resulting in sex-specific analyses. In the females model, results showed lower adjusted mean BMI for those meeting MSA only (b = -1.05 kg/m2, p = .0215), APA only (b = -1.14 kg/m2, p = .0014), or both APA and MSA (b = -1.84 kg/m2, p < .0001) guideline. Additionally, mean BMI decreased in dose-response fashion (p for trend < .0001) for females. In the males model, results showed lower adjusted mean BMI (b = -0.77 kg/m2, p = .0077) for those meeting both APA and MSA only.

4. Discussion

The purpose of this study was to examine how meeting different PA guideline parameters relate to BMI in adults. Results clearly indicate that meeting either PA guideline is associated with lower BMI and remains so after full sociodemographic adjustment. Several specific findings however are worth discussing. Firstly, these data indicate that meeting both APA and MSA relates to more than twice the effect on BMI as compared to meeting APA only. This finding supports the 2018 recommendation for adults, which promotes both guidelines, in terms of maintaining a healthy body weight 21. Secondly, overall, meeting MSA guidelines only was not related to BMI when compared to being inactive. There are two possible explanations for this finding. One is that adults participating in MSA may have similar BMI to inactive adults, but because they have more muscle mass, which in turn increases body mass and BMI 22. Although this is a familiar argument, it does not explain why those meeting both APA and MSA have such lower BMI than their MSA only and inactive counterparts. Two is that the low relative sample size for adults meeting MSA only decreased the chances of finding an MSA only effect on BMI 23. Regardless, however, the effect size for this relationship was smaller than its comparison categories. Thirdly, similar to the previous note, adults classified as insufficiently active had similar BMI to those classified as inactive. This finding supports the 150+ minutes of moderate-intensity (or vigorous-intensity equivalent) APA threshold recommended of all adults. Lastly, sex-specific analyses on the four-level PA guideline parameter showed that meeting either APA only or MSA only as well as meeting both APA and MSA related to lower BMI in females. Conversely, in males, lower BMI was only associated with meeting both APA and MSA guidelines. Despite these findings, an indirect dose-response relationship was seen in females, where meeting MSA only had the smallest effect on BMI, meeting APA only had a slightly larger effect on BMI, and meeting both APA and MSA had a pretty substantial effect on BMI. Therefore, although meeting either PA guideline was seen to have BMI benefit, meeting both guidelines should be considered optimal in both male and female adults.

5. Conclusions

This study found that meeting either APA or MSA guideline is associated with lower BMI in adults. However, sex-specific analyses indicate that this is true for females only and in dose-response fashion. Lower BMI in males is only associated with meeting both APA and MSA guidelines. Health promotion specialists concerned with obesity should understand the influence that each PA guideline has on relative body weight. Physical activity programming should promote both APA and MSA among adults in Montana.

References

[1]  Office of Disease Prevention and Health Promotion. (n.d.). Overweight and Obesity. Healthy People 2030. U.S. Department of Health and Human Services. https://health.gov/healthypeople/objectives-and-data/browse-objectives/overweight-and-obesity.
In article      
 
[2]  Kwon S, Wang M, Hawkins M. Association between self-reported physical activity and obesity among White, Black, Hispanic, and Asian Americans: 2007 and 2009 brfss. Ethnicity & Disease. 2013; 23(2): 129-35.
In article      
 
[3]  Dun Q, Duan Y, Fu M, Meng H, Xu W, Yu T, Debra D, Tu N, Li X, Ma L, Du Y. Built environment, physical activity, and obesity of adults in Pingshan District, Shenzhen City in Southern China. Annals of Human Biology. 2021 Jan 2; 48(1): 15-22.
In article      View Article  PubMed
 
[4]  Cárdenas Fuentes G, Bawaked RA, Martínez González MÁ, Corella D, Subirana Cachinero I, Salas-Salvadó J, Estruch R, Serra-Majem L, Ros E, Lapetra Peralta J, Fiol M. Association of physical activity with body mass index, waist circumference and incidence of obesity in older adults. European journal of public health. 2018 Oct 1; 28(5): 944-50.
In article      View Article  PubMed
 
[5]  Fátima M Madrona Marcos 1, Josefa M Panisello Royo, Julio A Carbayo Herencia, Josep Alins, Loreto Tárraga Marcos, Eudald Castell Panisello, Pedro J Tárraga López. Motivational intervention for obesity in Primary Care using a physical activity program. Nutricion Hospitalaria. 2020 Feb 14.
In article      
 
[6]  Beavers KM, Beavers DP, Nesbit BA, Ambrosius WT, Marsh AP, Nicklas BJ, Rejeski WJ. Effect of an 18-month physical activity and weight loss intervention on body composition in overweight and obese older adults. Obesity. 2014 Feb; 22(2): 325-31.
In article      View Article  PubMed
 
[7]  McArdle WD, Katch FI, Katch VL. Exercise physiology: nutrition, energy, and human performance. Lippincott Williams & Wilkins; 2010.
In article      
 
[8]  Lee YY, Kamarudin KS, Muda WA. Associations between self-reported and objectively measured physical activity and overweight/obesity among adults in Kota Bharu and Penang, Malaysia. BMC public health. 2019 Dec; 19(1): 1-2.
In article      View Article  PubMed
 
[9]  Burns RJ, Fillo J, Deschênes SS, Schmitz N. Dyadic associations between physical activity and body mass index in couples in which one partner has diabetes: results from the Lifelines cohort study. Journal of behavioral medicine. 2020 Feb; 43(1): 143-9.
In article      View Article  PubMed
 
[10]  Al-Ajlan AR, Mehdi SR. Effects and a dose response relationship of physical activity to high density lipoprotein cholesterol and body mass index among Saudis. Saudi medical journal. 2005 Jul 1; 26(7): 1107-11.
In article      
 
[11]  Piercy KL, Troiano RP. Physical activity guidelines for Americans from the US department of health and human services: Cardiovascular benefits and recommendations. Circulation: Cardiovascular Quality and Outcomes. 2018 Nov; 11(11): e005263.
In article      View Article  PubMed
 
[12]  Tran L, Tran P, Tran L. A cross-sectional examination of sociodemographic factors associated with meeting physical activity recommendations in overweight and obese US adults. Obesity research & clinical practice. 2020 Jan 1; 14(1): 91-8.
In article      View Article  PubMed
 
[13]  Littman AJ, Jacobson IG, Boyko EJ, Smith TC. Changes in meeting physical activity guidelines after discharge from the military. Journal of Physical Activity and Health. 2015 May 1; 12(5): 666-74.
In article      View Article  PubMed
 
[14]  Aparicio-Ting FE, Friedenreich CM, Kopciuk KA, Plotnikoff RC, Bryant HE. Prevalence of meeting physical activity guidelines for cancer prevention in Alberta. Chronic diseases and injuries in Canada. 2012 Sep 1; 32(4).
In article      View Article  PubMed
 
[15]  Centers for Disease Control and Prevention. The BRFSS data user guide. August 15, 2013.
In article      
 
[16]  Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System Overview: BRFSS 2019. July 26, 2019.
In article      
 
[17]  SAS Institute Inc. 2015. SAS/STAT® 14.1 User’s Guide. Cary, NC: SAS Institute Inc.
In article      
 
[18]  IBM Corp. Released 2020. IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp.
In article      
 
[19]  Zou D, Lloyd JE, Baumbusch JL. Using SPSS to analyze complex survey data: a primer. Journal of Modern Applied Statistical Methods. 2020; 18(1): 16.
In article      View Article
 
[20]  Siller AB, Tompkins L. The big four: Analyzing complex sample survey data using SAS, SPSS, STATA, and SUDAAN. Inproceedings of the thirty-first annual SAS® Users Group international conference 2006 Mar 27 (pp. 26-29).
In article      
 
[21]  2018 Physical Activity Guidelines Advisory Committee. 2018 Physical Activity Guidelines Advisory Committee Scientific Report. Washington, DC: U.S. Department of Health and Human Services, 2018.
In article      
 
[22]  Kenney WL, Wilmore JH, Costill DL. Physiology of sport and exercise. Human kinetics; 2015 May 19.
In article      
 
[23]  Gravetter FJ, Wallnau LB. Statistics for the behavioral sciences. 10th Edition. Belmont. CA: Thomson Wadsworth. 2017.
In article      
 

Published with license by Science and Education Publishing, Copyright © 2021 Peter D. Hart

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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Normal Style
Peter D. Hart. Relationship between Meeting Physical Activity Guideline Parameters and Body Mass Index (BMI) in Adults. Journal of Physical Activity Research. Vol. 6, No. 2, 2021, pp 130-134. http://pubs.sciepub.com/jpar/6/2/11
MLA Style
Hart, Peter D.. "Relationship between Meeting Physical Activity Guideline Parameters and Body Mass Index (BMI) in Adults." Journal of Physical Activity Research 6.2 (2021): 130-134.
APA Style
Hart, P. D. (2021). Relationship between Meeting Physical Activity Guideline Parameters and Body Mass Index (BMI) in Adults. Journal of Physical Activity Research, 6(2), 130-134.
Chicago Style
Hart, Peter D.. "Relationship between Meeting Physical Activity Guideline Parameters and Body Mass Index (BMI) in Adults." Journal of Physical Activity Research 6, no. 2 (2021): 130-134.
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  • Figure 1. Mean BMI across 4-level PA guidelines status by sex in Montana adults, 2019 (Note. N = 4,596. Body mass index (BMI) computed from self-reported height and weight (kg/m2). Adjusted unstandardized slopes (bs) are by sex and controlled for age, race/ethnicity, income, education, and rural/urban status. Slope values in bold are significantly (p < .05) different from their sex-specific reference (ref). Population restricted to BMI < 40 kg/m2.)
  • Table 1. Body mass index (BMI) comparison by aerobic physical activity (APA) guideline status in Montana adults, 2019
  • Table 2. Body mass index (BMI) comparison by muscle strengthening activity (MSA) guideline status in Montana adults, 2019
  • Table 3. Body mass index (BMI) regressed on the different meeting PA guideline parameters in Montana adults, 2019
[1]  Office of Disease Prevention and Health Promotion. (n.d.). Overweight and Obesity. Healthy People 2030. U.S. Department of Health and Human Services. https://health.gov/healthypeople/objectives-and-data/browse-objectives/overweight-and-obesity.
In article      
 
[2]  Kwon S, Wang M, Hawkins M. Association between self-reported physical activity and obesity among White, Black, Hispanic, and Asian Americans: 2007 and 2009 brfss. Ethnicity & Disease. 2013; 23(2): 129-35.
In article      
 
[3]  Dun Q, Duan Y, Fu M, Meng H, Xu W, Yu T, Debra D, Tu N, Li X, Ma L, Du Y. Built environment, physical activity, and obesity of adults in Pingshan District, Shenzhen City in Southern China. Annals of Human Biology. 2021 Jan 2; 48(1): 15-22.
In article      View Article  PubMed
 
[4]  Cárdenas Fuentes G, Bawaked RA, Martínez González MÁ, Corella D, Subirana Cachinero I, Salas-Salvadó J, Estruch R, Serra-Majem L, Ros E, Lapetra Peralta J, Fiol M. Association of physical activity with body mass index, waist circumference and incidence of obesity in older adults. European journal of public health. 2018 Oct 1; 28(5): 944-50.
In article      View Article  PubMed
 
[5]  Fátima M Madrona Marcos 1, Josefa M Panisello Royo, Julio A Carbayo Herencia, Josep Alins, Loreto Tárraga Marcos, Eudald Castell Panisello, Pedro J Tárraga López. Motivational intervention for obesity in Primary Care using a physical activity program. Nutricion Hospitalaria. 2020 Feb 14.
In article      
 
[6]  Beavers KM, Beavers DP, Nesbit BA, Ambrosius WT, Marsh AP, Nicklas BJ, Rejeski WJ. Effect of an 18-month physical activity and weight loss intervention on body composition in overweight and obese older adults. Obesity. 2014 Feb; 22(2): 325-31.
In article      View Article  PubMed
 
[7]  McArdle WD, Katch FI, Katch VL. Exercise physiology: nutrition, energy, and human performance. Lippincott Williams & Wilkins; 2010.
In article      
 
[8]  Lee YY, Kamarudin KS, Muda WA. Associations between self-reported and objectively measured physical activity and overweight/obesity among adults in Kota Bharu and Penang, Malaysia. BMC public health. 2019 Dec; 19(1): 1-2.
In article      View Article  PubMed
 
[9]  Burns RJ, Fillo J, Deschênes SS, Schmitz N. Dyadic associations between physical activity and body mass index in couples in which one partner has diabetes: results from the Lifelines cohort study. Journal of behavioral medicine. 2020 Feb; 43(1): 143-9.
In article      View Article  PubMed
 
[10]  Al-Ajlan AR, Mehdi SR. Effects and a dose response relationship of physical activity to high density lipoprotein cholesterol and body mass index among Saudis. Saudi medical journal. 2005 Jul 1; 26(7): 1107-11.
In article      
 
[11]  Piercy KL, Troiano RP. Physical activity guidelines for Americans from the US department of health and human services: Cardiovascular benefits and recommendations. Circulation: Cardiovascular Quality and Outcomes. 2018 Nov; 11(11): e005263.
In article      View Article  PubMed
 
[12]  Tran L, Tran P, Tran L. A cross-sectional examination of sociodemographic factors associated with meeting physical activity recommendations in overweight and obese US adults. Obesity research & clinical practice. 2020 Jan 1; 14(1): 91-8.
In article      View Article  PubMed
 
[13]  Littman AJ, Jacobson IG, Boyko EJ, Smith TC. Changes in meeting physical activity guidelines after discharge from the military. Journal of Physical Activity and Health. 2015 May 1; 12(5): 666-74.
In article      View Article  PubMed
 
[14]  Aparicio-Ting FE, Friedenreich CM, Kopciuk KA, Plotnikoff RC, Bryant HE. Prevalence of meeting physical activity guidelines for cancer prevention in Alberta. Chronic diseases and injuries in Canada. 2012 Sep 1; 32(4).
In article      View Article  PubMed
 
[15]  Centers for Disease Control and Prevention. The BRFSS data user guide. August 15, 2013.
In article      
 
[16]  Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System Overview: BRFSS 2019. July 26, 2019.
In article      
 
[17]  SAS Institute Inc. 2015. SAS/STAT® 14.1 User’s Guide. Cary, NC: SAS Institute Inc.
In article      
 
[18]  IBM Corp. Released 2020. IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp.
In article      
 
[19]  Zou D, Lloyd JE, Baumbusch JL. Using SPSS to analyze complex survey data: a primer. Journal of Modern Applied Statistical Methods. 2020; 18(1): 16.
In article      View Article
 
[20]  Siller AB, Tompkins L. The big four: Analyzing complex sample survey data using SAS, SPSS, STATA, and SUDAAN. Inproceedings of the thirty-first annual SAS® Users Group international conference 2006 Mar 27 (pp. 26-29).
In article      
 
[21]  2018 Physical Activity Guidelines Advisory Committee. 2018 Physical Activity Guidelines Advisory Committee Scientific Report. Washington, DC: U.S. Department of Health and Human Services, 2018.
In article      
 
[22]  Kenney WL, Wilmore JH, Costill DL. Physiology of sport and exercise. Human kinetics; 2015 May 19.
In article      
 
[23]  Gravetter FJ, Wallnau LB. Statistics for the behavioral sciences. 10th Edition. Belmont. CA: Thomson Wadsworth. 2017.
In article