- Email: [email protected]
Physical Activity and Abnormal Blood Glucose Among Healthy Weight Adults
RESEARCH ARTICLE
Physical Activity and Abnormal Blood Glucose Among Healthy Weight Adults Arch G. Mainous III, PhD,1,2 Rebecca J. Tanner, MA,1 Stephen D. Anton, PhD,3 Ara Jo, MS,1 Maya C. Luetke, MSPH1 Introduction: Physical activity has been linked to prevention and treatment of prediabetes and diabetes in overweight and obese adults. This study examines the relationship between low physical activity levels and risk of abnormal blood glucose (prediabetes or undiagnosed diabetes) in healthy weight adults.
Methods: Data from the 2014 Health Survey for England were analyzed in July 2016, focusing on adults with a BMI Z18.5 and o25 who had never been diagnosed with diabetes (N¼1,153). Abnormal blood glucose was defined as hemoglobin A1c Z5.7. Physical activity was measured through the International Physical Activity Questionnaire. Bivariate analyses and Poisson models were conducted on the effect of physical activity on abnormal blood glucose, controlling for age, sex, waist to hip ratio, sitting time, age X physical activity interaction, sex X physical activity, and race. Results: Abnormal blood glucose was detected in 23.7% of individuals with low activity levels, 14.8% of those with medium activity levels, and 12.2% of those with high activity levels (po0.003). Similarly, 25.4% of inactive individuals (physically active for o30 minutes per week) were more likely to have abnormal blood glucose levels than active individuals (13.4%, po0.0001). Higher physical activity was associated with a lower likelihood of abnormal blood glucose in an adjusted Poisson regression. Conclusions: Among healthy weight adults, low physical activity levels are significantly associated with abnormal blood glucose (prediabetes and undiagnosed diabetes). These findings suggest that healthy weight individuals may benefit from physical exercise. Am J Prev Med 2016;](]):]]]–]]]. & 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
INTRODUCTION
D
iabetes has reached epidemic proportions. Worldwide, the number of people with diabetes has risen from 108 million in 1980 to 422 million in 2014.1 Diabetes is a major cause of kidney failure, heart attacks, stroke, and lower limb amputations.2 In addition to the morbidity and mortality associated with diabetes, the cost of diabetes care is substantial.3 Early detection and screening for undiagnosed Type 2 diabetes is needed because of the utility of treatment to prevent Type 2 diabetes complications.4 Second, there is an equal or more important need to detect prediabetes, a state of abnormal blood glucose that indicates high risk for the development of Type 2 diabetes.5 Strategies for
detection of abnormal glucose tend to focus on individuals who are overweight or obese.4,6 Recent data have indicated, however, that a substantial proportion of individuals at a “healthy weight” (BMI between 18.5 and 24.9) have prediabetes.7 In fact, among healthy weight individuals aged 45 years and older in the U.S., From the 1Department of Health Services Research, Management and Policy, University of Florida, Gainesville, Florida; 2Department of Community Health and Family Medicine, University of Florida, Gainesville, Florida; and 3Department of Aging and Geriatric Research, University of Florida, Gainesville, Florida Address correspondence to: Arch G. Mainous III, PhD, Department of Health Services Research, Management, and Policy, University of Florida, Health Sciences Center, PO Box 100195, Gainesville FL 32610. E-mail: [email protected]fl.edu. 0749-3797/$36.00 http://dx.doi.org/10.1016/j.amepre.2016.11.027
& 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
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the prevalence of prediabetes was 33.1% in 2012.7 One theory for this substantial proportion of healthy weight, prediabetic adults in the U.S. is that sedentary lifestyle may contribute to unhealthy changes in body composition, even among individuals who are not overweight. Some individuals at healthy weights have what has been referred to as “normal-weight obesity,” a condition characterized by high body fat and lower lean muscle mass while still falling within the BMI parameters of “healthy” weight.8 This study is innovative in examining abnormal blood glucose in healthy weight adults, a population previously believed to be at low risk of glucose abnormalities. Because typical strategies to prevent prediabetes or Type 2 diabetes (e.g., calorie restriction and weight reduction) are inappropriate for individuals who are not overweight, it is unclear whether physical activity moderates the presence of abnormal glucose in this healthy weight population. The purpose of this study was to examine the relationship of physical activity with abnormal blood glucose among adults at a healthy weight who previously had not been diagnosed with diabetes.
METHODS Data from the 2014 Health Survey for England (HSE) were analyzed. The HSE is an annual survey that monitors trends in the health of England’s residents. The HSE uses a stratified random probability sample of households. Information on the sampling methodology of the HSE is available from the United Kingdom Data Service.9 The HSE includes both a computer-assisted personal interview and a nurse visit. For the 2014 HSE, of those respondents with full interviews, 5,941 adults aged Z16 years and 1,249 children aged 0–15 years had a visit with a nurse.9 During the nurse visit, a nurse obtained blood, saliva, and urine samples, along with physical measurements of the participant. To obtain accurate estimates, the HSE is weighted by the Joint Health Surveys Unit of NatCen Social Research and University College London to account for sampling design, non-response, and the type of data used.10,11 Using the weighting variable allows researchers to make estimates for the entire population in England and reduce possible biases.9 The current project focused on adults aged Z20 years, who had a nurse-measured BMI Z18.5 and o25, who reported never being diagnosed with diabetes, and who had data available on glycated hemoglobin (HbA1c). Based on these criteria, there were a total of 1,153 respondents (weighted sample size, 1,219). The weighted sample size is the sample size when the weighting variable is applied to the sample. Data were analyzed in July 2016. The study used publicly available de-identified data and was exempted by the University of Florida IRB.
Measures Individuals were considered to have diagnosed diabetes if they reported that they had been diagnosed with diabetes (other than gestational) by a healthcare provider.
Participants with abnormal blood glucose were identified using HbA1c. Abnormal blood glucose was defined as HbA1c Z5.7%.6 Owing to their increased risk of all-cause mortality, individuals with HbA1c o4.0 were removed from the analysis.12 On August 4, 2016, HSE 2014 users were notified of the need to correct a calibration problem with the HbA1c values in the HSE for 2014 (K Dennison, UK Data Service, personal/written communication, 2016). The HbA1c levels used for this paper have been corrected as recommended by NatCen Social Research, the organization that jointly conducts the HSE on behalf of the Health and Social Care Information Centre. For HbA1c values between 3.5 and 6.62, 0.1 was added to the given HbA1c level. For HbA1c values between 6.3 and 8.9, 0.2 was added to the given HbA1c level. For HbA1c values 48.9, 0.3 was added to the given HbA1c level. There were 953 individuals of normal BMI who did not have diabetes and were aged 420 years and did not have HbA1c results. Although this has the potential to introduce bias, the weighting variable took into account respondents who refused or were unable to give a blood sample to partially mitigate the effect of missing data. Physical activity was defined in two ways. First, the HSE includes a derived variable of tertiles of moderate or vigorous intensive minutes of activity per week based on the International Physical Activity Questionnaire questions in the HSE.13 The tertiles are sex specific, and exclude walking.14 Activity level is characterized as low, medium, and high. For men, low physical activity was 0–120 minutes of moderate- to vigorous-intensity physical activity (MVPA) per week; medium MVPA was 121–840 minutes per week; and high MVPA was Z841 minutes of MVPA per week. For women, low MVPA was defined as 0 minutes of MVPA per week, medium MVPA was defined as between 10 and 496 minutes of MVPA, and high MVPA was defined as Z496 minutes MVPA per week.15 The HSE MVPA measures included some values that were extremely high. Out of concern that these extremely high and unrealistic values would bias the analysis, respondents reporting 45,000 minutes of MVPA per week were excluded from the analysis. In doing so, 26 respondents were recoded as missing. Additionally, of individuals aged Z20 years with available HbA1c measures and a normal BMI, a total of 156 were missing data on physical activity. The second way physical activity was operationalized was whether a person was active Z30 minutes per week, according to their responses on the International Physical Activity Questionnaire. Individuals were considered either active (Z30 minutes of MVPA per week) or inactive (o30 minutes MVPA per week). Sitting time was analyzed. The HSE asks respondents how many minutes they usually spend sitting on a weekday. Waist to hip ratio (WHR) was assessed because of its utility as a measure of abdominal obesity, which has been associated with metabolic problems.14,16,17 The HSE includes a derived variable, mean WHR. Waist circumference was measured midway between the iliac crest and the costal margin twice.9 The hip circumference was measured at the widest circumference over the buttocks and below the iliac crest twice.9 The means of each number were used to create a mean WHR.9 A WHR 40.85 in women or 40.90 in men was considered unhealthy.18 For this analysis, respondents were split into two age groups, those aged 20–44 years and those aged Z45 years. The American Diabetes Association recommends screening for abnormal blood glucose for all adults aged 445 years, as the risk of developing diabetes increases with age.4 Race/ethnicity was categorized as white, Asian, and other. Sex was defined as male and female. www.ajpmonline.org
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Statistical Analysis
Table 2. Physical Activity Characteristics
This study used SAS, version 9.4, for all analyses. Bivariate analyses were conducted on the relationship between physical activity and abnormal blood glucose. The sample was stratified based on sex and age, examining the bivariate relationships among men and women and for those aged 20–44 years and Z45 years. Unadjusted Poisson models with robust SEs were computed examining the effect of each physical activity variable on abnormal blood glucose. Adjusted Poisson models with robust SEs were computed examining the effect of each physical activity variable on abnormal blood glucose, controlling for age, sex, WHR, sitting time, age X physical activity interaction, and sex X physical activity interaction. To check for potential multicollinearity between physical activity variables and sitting time, the correlation between sitting time and minutes of MVPA per week was computed. The correlation was –0.15. All analyses were weighted using the weight appropriate for variables derived from the blood sample to account for survey design and non-response. The weighting variable allowed the authors to make estimates of the English population.9
RESULTS The sample comprised adults aged Z20 years who had not been diagnosed with diabetes by a healthcare provider and had a healthy BMI. Tables 1 and 2 show the demographic and physical activity characteristics of the sample. The relationship between abnormal blood glucose and MVPA tertile was statistically significant (p=0.0003). Among individuals with low MVPA, 23.7% had abnormal blood glucose compared with 14.8% of those with medium MVPA, and 12.2% of those with high MVPA. Among men, physical activity level was significantly associated with abnormal blood glucose (p=0.003). Among men with low MVPA, 23.7% had abnormal blood glucose, compared with those with Table 1. Demographic Characteristics (Unweighted Sample Size 1,153; Weighted Sample Size¼1,219)
Characteristic Age, years 20–44 Z45 Sex Male Female Race White Asian Other Unhealthy WHR Abnormal blood glucose
% of sample
Lowest activity tertile
Middle activity tertile
Highest activity tertile
58.8 41.2
53.1 46.9
62.2 37.8
62.0 38.0
44.4 55.6
41.7 58.3
42.0 46.1
58.0 53.9
89.1 7.3 3.6 21.2 16.8
87.2 10.6 2.2 33.3 23.7
91.3 4.7 4.0 19.5 14.8
89.8 7.4 2.8 12.4 12.2
WHR, waist to hip ratio.
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Characteristic Physical activity tertile Low activity Medium activity High activity Physical activity level Inactive/o30 minutes’ MVPA per week Z30 minutes’ MVPA per week Usual minutes sitting per weekday r270 4270
% of sample 26.2 38.8 35.0 23.3 76.7 47.2 52.8
MVPA, moderate to vigorous physical activity.
medium MVPA (12.4%) and high MVPA (9.9%). Among women, the relationship between activity level and abnormal blood glucose was not statistically significant (low MVPA, 23.6%; medium MVPA, 16.5%; high MVPA, 14.2%; p=0.06). Among those aged 20–44 years, there was not a significant difference in abnormal blood glucose by activity level (low MVPA, 6.1%; medium MVPA, 5.8%; high MVPA, 3.0%; p=0.25). Among adults aged Z45 years, there was a significant difference in the proportion with abnormal blood glucose between activity levels (low MVPA, 43.5%; medium MVPA, 29.5%; high MVPA, 27.3%; p=0.009). Table 3 shows the prevalence ratios from adjusted and unadjusted Poisson regression models examining the effect of MVPA tertile on abnormal blood glucose. The results of Poisson regression models indicated that low physical activity was associated with the presence of abnormal blood glucose. The adjusted results presented here do not include the age X physical activity or sex X physical activity interaction terms as they were not significant in the model. There was a statistically significant difference in blood glucose levels between inactive and active individuals. Among inactive individuals (those physically active for o30 minutes per week), 25.4% had abnormal blood glucose compared with 13.4% of those who had Z30 minutes of MVPA per week (po0.0001). Among men, physical activity level was significantly associated with abnormal blood glucose (po0.0001). Among inactive men, 29.4% had abnormal blood glucose, compared with 11.0% among men with Z30 minutes of MVPA per week (po0.0001). Among women, the relationship between activity level and abnormal blood glucose was also significant, with 23.5% of inactive women with abnormal blood glucose compared with 15.5% of women with Z30 minutes of MVPA per week (p¼0.02). Among those aged 20–44 years, there was not a significant difference in abnormal blood glucose by
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Table 3. Unadjusted and Adjusted Prevalence Ratios for Physical Activity Predicting Abnormal Blood Glucose
Model Unadjusted results Physical activity tertiles Low physical activity Medium physical activity High physical activity Physical activity level Inactive/o30 minutes per week Active for Z30 minutes per week Adjusted results Physical activity tertilesa Low physical activity Medium physical activity High physical activity Physical activity levelb Inactive/o30 minutes per week Active for Z30 minutes per week
Prevalence ratio (95% CI)
1.94 (1.35, 2.78) 1.21 (0.84, 1.75) 1.00 1.90 (1.41, 2.56) 1.00
1.48 (1.04, 2.11) 1.15 (0.81, 1.64) 1.00 1.66 (1.02, 2.70) 1.00
a
Adjusted for age, sex, race, sitting time, unhealthy WHR. Adjusted for age, sex, age X physical activity interaction, sex X physical activity interaction, race, sitting time, unhealthy WHR. WHR, waist to hip ratio. b
physical activity versus inactivity (inactive, 7.0%; Z30 minutes of MVPA, 4.3%; p¼0.21). Among adults aged Z45 years, there was a significant difference in the proportion with abnormal blood glucose between physical activity and inactivity (inactive, 45.7%; Z30 minutes of MVPA, 28.3%; p¼0.0006). Table 3 shows the prevalence ratios from adjusted and unadjusted Poisson regression models examining the effect of physical activity versus inactivity on abnormal blood glucose. Being inactive was associated with an increased prevalence of abnormal blood glucose. These presented results do include the interaction terms for age X physical activity and sex X physical activity. Men who were inactive had a higher prevalence ratio of abnormal blood glucose than men who were active (1.95, 95% CI¼1.05, 3.60). Respondents aged Z45 years who were inactive also had a higher prevalence ratio of abnormal blood glucose (1.52, 95% CI¼1.14, 2.03).
DISCUSSION The key finding of this study is that low physical activity levels are associated with abnormal blood glucose in healthy weight adults. These results help us to better understand a potential intervention for healthy weight individuals who may not be metabolically healthy. Further, these results from England add to previous findings from the U.S. on the increasing prevalence of abnormal blood glucose among healthy weight adults.7
These findings are consistent with previous evidence that healthy weight populations with lower physical activity levels exhibit higher Type 2 diabetes prevalence rates.19 Previous studies have found that low physical activity contributes to risk of prediabetes or Type 2 diabetes.20–22 However, these have focused almost exclusively on overweight/obese populations. This is one of the first studies that looks at diabetes prevalence and physical activity in the healthy weight population. Insulin sensitivity and other metabolic improvements have been associated with exercise-induced visceral fat loss, rather than overall weight loss.23,24 Further, targeted exercise programs have been shown to relieve symptoms and comorbidities in adults with Type 2 diabetes regardless of weight loss.25 Therefore, it is important to examine the phenomenon of abnormal blood glucose in healthy weight individuals and to investigate the effect of physical activity on the blood glucose levels of these individuals. Exercise has been shown to be a modifiable and costeffective lifestyle intervention in reducing unnecessary weight gain and controlling blood glucose.26–28 Historically, the focus of Type 2 diabetes prevention and treatment programs has been primarily on calorie restriction and weight loss. However, this study and others suggest that physical activity, not solely weight loss, provides the protective and therapeutic effects on blood glucose levels.29,30 Accordingly, physical activity should be a crucial tenet of future prevention interventions, especially in the healthy weight population. Studies have shown that physical activity boosts resting metabolic rates and increases lean muscle mass, which have been linked to improved insulin action.31–33 Muscle strength, decreases in visceral adiposity, and improved insulin sensitivity have all been associated with higher levels of physical activity.34,35 Future studies should investigate diabetes risk, exercise, lean muscle mass, and visceral adiposity in healthy weight individuals. Two different measures of physical activity were used. Physical activity is a more general concept than exercise, which refers to structured or planned activities, and is commonly evaluated as leisure time exercise. Many of the recommendations on physical activity are actually focused on the subset of activity for leisure time exercise, thereby missing activity in the workplace.36 In this study using two different measures of physical activity, both measures produced similar results, showing that a healthy weight population with low levels of physical activity is more likely to have prediabetes or undiagnosed Type 2 diabetes than those who report higher levels of physical activity. This finding provides support for the association of low levels of physical activity with increased prevalence of abnormal blood glucose among www.ajpmonline.org
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this population. In these results, differences between physical activity tertiles were significant in men but not in women. This difference in significance between sexes could be due to not having a large enough sample size for women or because there may be an optimal level that men, who were more active, were more likely to meet than women. Similarly, the fact that results were significant in the population aged Z45 years but not in the population aged 20–44 years is likely the result of the recognized effect of aging on Type 2 diabetes risk.4,6 Additionally, when terms accounting for the interaction between age and physical activity and sex and physical activity were evaluated, the association between physical activity and abnormal blood glucose was only apparent in men with no activity in the active versus inactive model and among those aged Z45 years with no activity in the same model.
Limitations The strength of the present study is the use of a nationally representative survey that includes biomarkers. It provides evidence from an industrialized country other than the U.S. This study also goes beyond the focus on overweight/obesity when examining abnormal blood glucose and covers new territory by looking at abnormal blood glucose in the healthy weight population.6 However, there are some limitations. First, although the physical activity variables were based on a valid and reliable scale, the International Physical Activity Questionnaire, it is based on self-reported data. Another limitation is that this study did not examine the impact of dietary factors. Third, the HSE did not collect data on family history of diabetes. Although family history can represent both culture and inherited predispositions, assessing the extent to which genetics plays a role in abnormal glucose among the healthy weight population was not within the analytic capabilities of the HSE. However, regardless of differences in diet and the genetic component of prediabetes and Type 2 diabetes, physical activity has been shown to elicit positive physiologic changes in blood glucose levels and insulin sensitivity.37,38 Another limitation is that it is possible that people with abnormal blood glucose might be sicker and thus less likely to engage in physical activity. However, a lack of physical activity has been shown to contribute to unhealthy blood glucose levels.39,40 Additionally, though sitting time was controlled for, the HSE did not allow for assessment of duration of sitting episodes. Finally, this study is cross-sectional and therefore does not examine the study variables over time. In order to further validate the connection between low physical activity levels and abnormal blood glucose in healthy weight individuals, an ] 2016
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RCT or an observational cohort study should be conducted.
CONCLUSIONS The present study provides strong evidence that physical activity levels are significantly associated with abnormal blood glucose in healthy weight adults. As noted above, this population has previously not been considered to be at high risk of abnormal blood glucose owing to their healthy BMI. However, these findings suggest that healthy weight individuals with low levels of activity represent a population with a higher prevalence of abnormal blood glucose than previously thought. An important next step is to examine how physical activity and other lifestyle interventions can effectively reduce the risk of abnormal blood glucose among individuals who are of healthy weight.
ACKNOWLEDGMENTS No financial disclosures were reported by the authors of this paper.
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Physical Activity and Abnormal Blood Glucose Among Healthy Weight Adults Arch G. Mainous III, PhD,1,2 Rebecca J. Tanner, MA,1 Stephen D. Anton, PhD,3 Ara Jo, MS,1 Maya C. Luetke, MSPH1 Introduction: Physical activity has been linked to prevention and treatment of prediabetes and diabetes in overweight and obese adults. This study examines the relationship between low physical activity levels and risk of abnormal blood glucose (prediabetes or undiagnosed diabetes) in healthy weight adults.
Methods: Data from the 2014 Health Survey for England were analyzed in July 2016, focusing on adults with a BMI Z18.5 and o25 who had never been diagnosed with diabetes (N¼1,153). Abnormal blood glucose was defined as hemoglobin A1c Z5.7. Physical activity was measured through the International Physical Activity Questionnaire. Bivariate analyses and Poisson models were conducted on the effect of physical activity on abnormal blood glucose, controlling for age, sex, waist to hip ratio, sitting time, age X physical activity interaction, sex X physical activity, and race. Results: Abnormal blood glucose was detected in 23.7% of individuals with low activity levels, 14.8% of those with medium activity levels, and 12.2% of those with high activity levels (po0.003). Similarly, 25.4% of inactive individuals (physically active for o30 minutes per week) were more likely to have abnormal blood glucose levels than active individuals (13.4%, po0.0001). Higher physical activity was associated with a lower likelihood of abnormal blood glucose in an adjusted Poisson regression. Conclusions: Among healthy weight adults, low physical activity levels are significantly associated with abnormal blood glucose (prediabetes and undiagnosed diabetes). These findings suggest that healthy weight individuals may benefit from physical exercise. Am J Prev Med 2016;](]):]]]–]]]. & 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
INTRODUCTION
D
iabetes has reached epidemic proportions. Worldwide, the number of people with diabetes has risen from 108 million in 1980 to 422 million in 2014.1 Diabetes is a major cause of kidney failure, heart attacks, stroke, and lower limb amputations.2 In addition to the morbidity and mortality associated with diabetes, the cost of diabetes care is substantial.3 Early detection and screening for undiagnosed Type 2 diabetes is needed because of the utility of treatment to prevent Type 2 diabetes complications.4 Second, there is an equal or more important need to detect prediabetes, a state of abnormal blood glucose that indicates high risk for the development of Type 2 diabetes.5 Strategies for
detection of abnormal glucose tend to focus on individuals who are overweight or obese.4,6 Recent data have indicated, however, that a substantial proportion of individuals at a “healthy weight” (BMI between 18.5 and 24.9) have prediabetes.7 In fact, among healthy weight individuals aged 45 years and older in the U.S., From the 1Department of Health Services Research, Management and Policy, University of Florida, Gainesville, Florida; 2Department of Community Health and Family Medicine, University of Florida, Gainesville, Florida; and 3Department of Aging and Geriatric Research, University of Florida, Gainesville, Florida Address correspondence to: Arch G. Mainous III, PhD, Department of Health Services Research, Management, and Policy, University of Florida, Health Sciences Center, PO Box 100195, Gainesville FL 32610. E-mail: [email protected]fl.edu. 0749-3797/$36.00 http://dx.doi.org/10.1016/j.amepre.2016.11.027
& 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
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the prevalence of prediabetes was 33.1% in 2012.7 One theory for this substantial proportion of healthy weight, prediabetic adults in the U.S. is that sedentary lifestyle may contribute to unhealthy changes in body composition, even among individuals who are not overweight. Some individuals at healthy weights have what has been referred to as “normal-weight obesity,” a condition characterized by high body fat and lower lean muscle mass while still falling within the BMI parameters of “healthy” weight.8 This study is innovative in examining abnormal blood glucose in healthy weight adults, a population previously believed to be at low risk of glucose abnormalities. Because typical strategies to prevent prediabetes or Type 2 diabetes (e.g., calorie restriction and weight reduction) are inappropriate for individuals who are not overweight, it is unclear whether physical activity moderates the presence of abnormal glucose in this healthy weight population. The purpose of this study was to examine the relationship of physical activity with abnormal blood glucose among adults at a healthy weight who previously had not been diagnosed with diabetes.
METHODS Data from the 2014 Health Survey for England (HSE) were analyzed. The HSE is an annual survey that monitors trends in the health of England’s residents. The HSE uses a stratified random probability sample of households. Information on the sampling methodology of the HSE is available from the United Kingdom Data Service.9 The HSE includes both a computer-assisted personal interview and a nurse visit. For the 2014 HSE, of those respondents with full interviews, 5,941 adults aged Z16 years and 1,249 children aged 0–15 years had a visit with a nurse.9 During the nurse visit, a nurse obtained blood, saliva, and urine samples, along with physical measurements of the participant. To obtain accurate estimates, the HSE is weighted by the Joint Health Surveys Unit of NatCen Social Research and University College London to account for sampling design, non-response, and the type of data used.10,11 Using the weighting variable allows researchers to make estimates for the entire population in England and reduce possible biases.9 The current project focused on adults aged Z20 years, who had a nurse-measured BMI Z18.5 and o25, who reported never being diagnosed with diabetes, and who had data available on glycated hemoglobin (HbA1c). Based on these criteria, there were a total of 1,153 respondents (weighted sample size, 1,219). The weighted sample size is the sample size when the weighting variable is applied to the sample. Data were analyzed in July 2016. The study used publicly available de-identified data and was exempted by the University of Florida IRB.
Measures Individuals were considered to have diagnosed diabetes if they reported that they had been diagnosed with diabetes (other than gestational) by a healthcare provider.
Participants with abnormal blood glucose were identified using HbA1c. Abnormal blood glucose was defined as HbA1c Z5.7%.6 Owing to their increased risk of all-cause mortality, individuals with HbA1c o4.0 were removed from the analysis.12 On August 4, 2016, HSE 2014 users were notified of the need to correct a calibration problem with the HbA1c values in the HSE for 2014 (K Dennison, UK Data Service, personal/written communication, 2016). The HbA1c levels used for this paper have been corrected as recommended by NatCen Social Research, the organization that jointly conducts the HSE on behalf of the Health and Social Care Information Centre. For HbA1c values between 3.5 and 6.62, 0.1 was added to the given HbA1c level. For HbA1c values between 6.3 and 8.9, 0.2 was added to the given HbA1c level. For HbA1c values 48.9, 0.3 was added to the given HbA1c level. There were 953 individuals of normal BMI who did not have diabetes and were aged 420 years and did not have HbA1c results. Although this has the potential to introduce bias, the weighting variable took into account respondents who refused or were unable to give a blood sample to partially mitigate the effect of missing data. Physical activity was defined in two ways. First, the HSE includes a derived variable of tertiles of moderate or vigorous intensive minutes of activity per week based on the International Physical Activity Questionnaire questions in the HSE.13 The tertiles are sex specific, and exclude walking.14 Activity level is characterized as low, medium, and high. For men, low physical activity was 0–120 minutes of moderate- to vigorous-intensity physical activity (MVPA) per week; medium MVPA was 121–840 minutes per week; and high MVPA was Z841 minutes of MVPA per week. For women, low MVPA was defined as 0 minutes of MVPA per week, medium MVPA was defined as between 10 and 496 minutes of MVPA, and high MVPA was defined as Z496 minutes MVPA per week.15 The HSE MVPA measures included some values that were extremely high. Out of concern that these extremely high and unrealistic values would bias the analysis, respondents reporting 45,000 minutes of MVPA per week were excluded from the analysis. In doing so, 26 respondents were recoded as missing. Additionally, of individuals aged Z20 years with available HbA1c measures and a normal BMI, a total of 156 were missing data on physical activity. The second way physical activity was operationalized was whether a person was active Z30 minutes per week, according to their responses on the International Physical Activity Questionnaire. Individuals were considered either active (Z30 minutes of MVPA per week) or inactive (o30 minutes MVPA per week). Sitting time was analyzed. The HSE asks respondents how many minutes they usually spend sitting on a weekday. Waist to hip ratio (WHR) was assessed because of its utility as a measure of abdominal obesity, which has been associated with metabolic problems.14,16,17 The HSE includes a derived variable, mean WHR. Waist circumference was measured midway between the iliac crest and the costal margin twice.9 The hip circumference was measured at the widest circumference over the buttocks and below the iliac crest twice.9 The means of each number were used to create a mean WHR.9 A WHR 40.85 in women or 40.90 in men was considered unhealthy.18 For this analysis, respondents were split into two age groups, those aged 20–44 years and those aged Z45 years. The American Diabetes Association recommends screening for abnormal blood glucose for all adults aged 445 years, as the risk of developing diabetes increases with age.4 Race/ethnicity was categorized as white, Asian, and other. Sex was defined as male and female. www.ajpmonline.org
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Statistical Analysis
Table 2. Physical Activity Characteristics
This study used SAS, version 9.4, for all analyses. Bivariate analyses were conducted on the relationship between physical activity and abnormal blood glucose. The sample was stratified based on sex and age, examining the bivariate relationships among men and women and for those aged 20–44 years and Z45 years. Unadjusted Poisson models with robust SEs were computed examining the effect of each physical activity variable on abnormal blood glucose. Adjusted Poisson models with robust SEs were computed examining the effect of each physical activity variable on abnormal blood glucose, controlling for age, sex, WHR, sitting time, age X physical activity interaction, and sex X physical activity interaction. To check for potential multicollinearity between physical activity variables and sitting time, the correlation between sitting time and minutes of MVPA per week was computed. The correlation was –0.15. All analyses were weighted using the weight appropriate for variables derived from the blood sample to account for survey design and non-response. The weighting variable allowed the authors to make estimates of the English population.9
RESULTS The sample comprised adults aged Z20 years who had not been diagnosed with diabetes by a healthcare provider and had a healthy BMI. Tables 1 and 2 show the demographic and physical activity characteristics of the sample. The relationship between abnormal blood glucose and MVPA tertile was statistically significant (p=0.0003). Among individuals with low MVPA, 23.7% had abnormal blood glucose compared with 14.8% of those with medium MVPA, and 12.2% of those with high MVPA. Among men, physical activity level was significantly associated with abnormal blood glucose (p=0.003). Among men with low MVPA, 23.7% had abnormal blood glucose, compared with those with Table 1. Demographic Characteristics (Unweighted Sample Size 1,153; Weighted Sample Size¼1,219)
Characteristic Age, years 20–44 Z45 Sex Male Female Race White Asian Other Unhealthy WHR Abnormal blood glucose
% of sample
Lowest activity tertile
Middle activity tertile
Highest activity tertile
58.8 41.2
53.1 46.9
62.2 37.8
62.0 38.0
44.4 55.6
41.7 58.3
42.0 46.1
58.0 53.9
89.1 7.3 3.6 21.2 16.8
87.2 10.6 2.2 33.3 23.7
91.3 4.7 4.0 19.5 14.8
89.8 7.4 2.8 12.4 12.2
WHR, waist to hip ratio.
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Characteristic Physical activity tertile Low activity Medium activity High activity Physical activity level Inactive/o30 minutes’ MVPA per week Z30 minutes’ MVPA per week Usual minutes sitting per weekday r270 4270
% of sample 26.2 38.8 35.0 23.3 76.7 47.2 52.8
MVPA, moderate to vigorous physical activity.
medium MVPA (12.4%) and high MVPA (9.9%). Among women, the relationship between activity level and abnormal blood glucose was not statistically significant (low MVPA, 23.6%; medium MVPA, 16.5%; high MVPA, 14.2%; p=0.06). Among those aged 20–44 years, there was not a significant difference in abnormal blood glucose by activity level (low MVPA, 6.1%; medium MVPA, 5.8%; high MVPA, 3.0%; p=0.25). Among adults aged Z45 years, there was a significant difference in the proportion with abnormal blood glucose between activity levels (low MVPA, 43.5%; medium MVPA, 29.5%; high MVPA, 27.3%; p=0.009). Table 3 shows the prevalence ratios from adjusted and unadjusted Poisson regression models examining the effect of MVPA tertile on abnormal blood glucose. The results of Poisson regression models indicated that low physical activity was associated with the presence of abnormal blood glucose. The adjusted results presented here do not include the age X physical activity or sex X physical activity interaction terms as they were not significant in the model. There was a statistically significant difference in blood glucose levels between inactive and active individuals. Among inactive individuals (those physically active for o30 minutes per week), 25.4% had abnormal blood glucose compared with 13.4% of those who had Z30 minutes of MVPA per week (po0.0001). Among men, physical activity level was significantly associated with abnormal blood glucose (po0.0001). Among inactive men, 29.4% had abnormal blood glucose, compared with 11.0% among men with Z30 minutes of MVPA per week (po0.0001). Among women, the relationship between activity level and abnormal blood glucose was also significant, with 23.5% of inactive women with abnormal blood glucose compared with 15.5% of women with Z30 minutes of MVPA per week (p¼0.02). Among those aged 20–44 years, there was not a significant difference in abnormal blood glucose by
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Table 3. Unadjusted and Adjusted Prevalence Ratios for Physical Activity Predicting Abnormal Blood Glucose
Model Unadjusted results Physical activity tertiles Low physical activity Medium physical activity High physical activity Physical activity level Inactive/o30 minutes per week Active for Z30 minutes per week Adjusted results Physical activity tertilesa Low physical activity Medium physical activity High physical activity Physical activity levelb Inactive/o30 minutes per week Active for Z30 minutes per week
Prevalence ratio (95% CI)
1.94 (1.35, 2.78) 1.21 (0.84, 1.75) 1.00 1.90 (1.41, 2.56) 1.00
1.48 (1.04, 2.11) 1.15 (0.81, 1.64) 1.00 1.66 (1.02, 2.70) 1.00
a
Adjusted for age, sex, race, sitting time, unhealthy WHR. Adjusted for age, sex, age X physical activity interaction, sex X physical activity interaction, race, sitting time, unhealthy WHR. WHR, waist to hip ratio. b
physical activity versus inactivity (inactive, 7.0%; Z30 minutes of MVPA, 4.3%; p¼0.21). Among adults aged Z45 years, there was a significant difference in the proportion with abnormal blood glucose between physical activity and inactivity (inactive, 45.7%; Z30 minutes of MVPA, 28.3%; p¼0.0006). Table 3 shows the prevalence ratios from adjusted and unadjusted Poisson regression models examining the effect of physical activity versus inactivity on abnormal blood glucose. Being inactive was associated with an increased prevalence of abnormal blood glucose. These presented results do include the interaction terms for age X physical activity and sex X physical activity. Men who were inactive had a higher prevalence ratio of abnormal blood glucose than men who were active (1.95, 95% CI¼1.05, 3.60). Respondents aged Z45 years who were inactive also had a higher prevalence ratio of abnormal blood glucose (1.52, 95% CI¼1.14, 2.03).
DISCUSSION The key finding of this study is that low physical activity levels are associated with abnormal blood glucose in healthy weight adults. These results help us to better understand a potential intervention for healthy weight individuals who may not be metabolically healthy. Further, these results from England add to previous findings from the U.S. on the increasing prevalence of abnormal blood glucose among healthy weight adults.7
These findings are consistent with previous evidence that healthy weight populations with lower physical activity levels exhibit higher Type 2 diabetes prevalence rates.19 Previous studies have found that low physical activity contributes to risk of prediabetes or Type 2 diabetes.20–22 However, these have focused almost exclusively on overweight/obese populations. This is one of the first studies that looks at diabetes prevalence and physical activity in the healthy weight population. Insulin sensitivity and other metabolic improvements have been associated with exercise-induced visceral fat loss, rather than overall weight loss.23,24 Further, targeted exercise programs have been shown to relieve symptoms and comorbidities in adults with Type 2 diabetes regardless of weight loss.25 Therefore, it is important to examine the phenomenon of abnormal blood glucose in healthy weight individuals and to investigate the effect of physical activity on the blood glucose levels of these individuals. Exercise has been shown to be a modifiable and costeffective lifestyle intervention in reducing unnecessary weight gain and controlling blood glucose.26–28 Historically, the focus of Type 2 diabetes prevention and treatment programs has been primarily on calorie restriction and weight loss. However, this study and others suggest that physical activity, not solely weight loss, provides the protective and therapeutic effects on blood glucose levels.29,30 Accordingly, physical activity should be a crucial tenet of future prevention interventions, especially in the healthy weight population. Studies have shown that physical activity boosts resting metabolic rates and increases lean muscle mass, which have been linked to improved insulin action.31–33 Muscle strength, decreases in visceral adiposity, and improved insulin sensitivity have all been associated with higher levels of physical activity.34,35 Future studies should investigate diabetes risk, exercise, lean muscle mass, and visceral adiposity in healthy weight individuals. Two different measures of physical activity were used. Physical activity is a more general concept than exercise, which refers to structured or planned activities, and is commonly evaluated as leisure time exercise. Many of the recommendations on physical activity are actually focused on the subset of activity for leisure time exercise, thereby missing activity in the workplace.36 In this study using two different measures of physical activity, both measures produced similar results, showing that a healthy weight population with low levels of physical activity is more likely to have prediabetes or undiagnosed Type 2 diabetes than those who report higher levels of physical activity. This finding provides support for the association of low levels of physical activity with increased prevalence of abnormal blood glucose among www.ajpmonline.org
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this population. In these results, differences between physical activity tertiles were significant in men but not in women. This difference in significance between sexes could be due to not having a large enough sample size for women or because there may be an optimal level that men, who were more active, were more likely to meet than women. Similarly, the fact that results were significant in the population aged Z45 years but not in the population aged 20–44 years is likely the result of the recognized effect of aging on Type 2 diabetes risk.4,6 Additionally, when terms accounting for the interaction between age and physical activity and sex and physical activity were evaluated, the association between physical activity and abnormal blood glucose was only apparent in men with no activity in the active versus inactive model and among those aged Z45 years with no activity in the same model.
Limitations The strength of the present study is the use of a nationally representative survey that includes biomarkers. It provides evidence from an industrialized country other than the U.S. This study also goes beyond the focus on overweight/obesity when examining abnormal blood glucose and covers new territory by looking at abnormal blood glucose in the healthy weight population.6 However, there are some limitations. First, although the physical activity variables were based on a valid and reliable scale, the International Physical Activity Questionnaire, it is based on self-reported data. Another limitation is that this study did not examine the impact of dietary factors. Third, the HSE did not collect data on family history of diabetes. Although family history can represent both culture and inherited predispositions, assessing the extent to which genetics plays a role in abnormal glucose among the healthy weight population was not within the analytic capabilities of the HSE. However, regardless of differences in diet and the genetic component of prediabetes and Type 2 diabetes, physical activity has been shown to elicit positive physiologic changes in blood glucose levels and insulin sensitivity.37,38 Another limitation is that it is possible that people with abnormal blood glucose might be sicker and thus less likely to engage in physical activity. However, a lack of physical activity has been shown to contribute to unhealthy blood glucose levels.39,40 Additionally, though sitting time was controlled for, the HSE did not allow for assessment of duration of sitting episodes. Finally, this study is cross-sectional and therefore does not examine the study variables over time. In order to further validate the connection between low physical activity levels and abnormal blood glucose in healthy weight individuals, an ] 2016
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RCT or an observational cohort study should be conducted.
CONCLUSIONS The present study provides strong evidence that physical activity levels are significantly associated with abnormal blood glucose in healthy weight adults. As noted above, this population has previously not been considered to be at high risk of abnormal blood glucose owing to their healthy BMI. However, these findings suggest that healthy weight individuals with low levels of activity represent a population with a higher prevalence of abnormal blood glucose than previously thought. An important next step is to examine how physical activity and other lifestyle interventions can effectively reduce the risk of abnormal blood glucose among individuals who are of healthy weight.
ACKNOWLEDGMENTS No financial disclosures were reported by the authors of this paper.
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