Abstract
BACKGROUND
The global prevalence of chronic noncommunicable diseases (NCDs) is on the rise, with the majority of the growth occurring among populations in developing countries. Few studies have quantified the health benefits for physical activity among sub-Saharan African adults. We examined associations of physical activity with the prevalence of metabolic syndrome (MetS) and its components in Ethiopian men and women.
METHODS
This cross-sectional study of 1,843 individuals (1,117 men and 726 women) was conducted among working adults (public schools and bank employees) in Addis Ababa, Ethiopia. The study was conducted in accordance with the STEPwise approach of the World Health Organization. Physical activity was assessed using a previously validated Global Physical Activity Questionnaire. MetS was defined according to the International Diabetes Federation criteria. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CI).
RESULTS
The odds of MetS was inversely associated with physical activity in men (P trend = 0.02) but not women (P trend = 0.85). Among men, the OR of MetS comparing those with high vs. low levels of physical activity was 0.56 (95% CI = 0.33–0.97). For women, the corresponding OR was 1.07 (95% CI = 0.57–2.01). Physical activity was significantly and inversely associated with high waist circumference and hypertriglyceridemia among men, but no such associations were observed among women.
CONCLUSIONS
Higher levels of physical activity were inversely associated with MetS and several individual components among men. No similar trends were observed among women in this cohort, in part because of the small sample size.
Keywords: Africa, blood pressure, global health, hypertension, metabolic syndrome, noncommunicable disease, physical activity.
Chronic noncommunicable diseases (NCDs), in particular cardiovascular diseases, type 2 diabetes, cancers, and chronic respiratory diseases, account for 60% of all deaths globally, more than double the number of deaths caused by infectious diseases, maternal and prenatal conditions, and nutritional deficiencies combined.1–3 The global prevalence of NCDs is on the rise, with the majority of the growth occurring among populations in developing countries.4 The rise in NCDs is driven in part by significant changes in dietary habits, physical activity levels, and tobacco consumption worldwide as a result of industrialization, urbanization, economic development, and food market globalization.1 Previous studies conducted in Ethiopia have documented a high prevalence of NCDs.5,6
Metabolic syndrome (MetS) is a constellation of risk factors of cardiovascular disease including diabetes, central obesity, hypertension, and dyslipidemia. Physical inactivity and obesity are 2 important determinants of MetS.4,7 Previous studies have shown that physically inactive persons have a 20%–30% increased risk of all-cause of mortality as compared with those who participate in 30 minutes of moderate intensity physical activity on most days of the week.8,9 Blood glucose impairment (hyperglycemia), excess abdominal/body fat (increased waist and/or obesity), dyslipidemia (low high-density lipoprotein cholesterol (HDL-C) and/or high triglycerides), and elevated blood pressure (BP) are the core criteria of MetS.10
Several studies have identified physical inactivity as one of the major proximate determinants of NCDs and MetS.4,7,11,12 Lee and colleagues recently highlighted the effect of physical inactivity on NCDs globally.11 The authors noted that physical inactivity can have an effect similar to that of other important NCD risk factors including cigarette smoking and obesity.11 Several African studies have reported the prevalence of MetS in urban populations. However, very few studies have quantified the relationship between physical inactivity and NCD risk among Africans, and no such studies exist in Ethiopian adults. Given this gap in the literature, and given the importance in developing health promotion and disease prevention programs in low- and middle-income countries, we examined associations of physical activity with the prevalence of MetS and its components in an occupational cohort of Ethiopian men and women.
METHODS
Study overview and participants
This cross-sectional study included regular employees of public schools and the Commercial Bank of Ethiopia in Addis Ababa. The study was conducted during the months of December 2009 and January 2010. Workplaces were selected based on institutional willingness to participate in the study and the large size and stability of their workforce. We reasoned understanding NCD risk among working urban dwellers would provide an opportunity to design health promotion and disease prevention programs. Multistage sampling was done by means of probability proportional to size sampling.13,14 The STEP-wise approach of the World Health Organization (WHO) for NCD surveillance in developing countries was used to characterize NCD risk factors in this study population.13 Briefly, the approach includes 3 levels of participant assessments: (i) questionnaire to gather demographic and behavioral information, (ii) simple physical measurements, and (iii) biochemical tests.13 After, excluding subjects with missing physical activity and anthropometric information (n = 123), pregnant women (n = 21), and individuals without laboratory measures (n = 227), a final sample size of 1,843 (1,117 men and 726 women) participants remained for analysis. Based on the demographic and lifestyle information provided, subjects excluded from analysis had similar characteristics to those considered.
Data collection
Data were collected by trained research interviewers using the WHO STEPS-structured questionnaire. The questionnaire was used to obtain data about the general sociodemographic composition of the population by asking age, sex, and education level.15 Some questions were added to supplement the WHO STEPS that are specific to local Ethiopian context. These additional questions were about behavioral risk factors such as khat consumption (a natural stimulant with amphetamine-like effects commonly used for social recreation in Ethiopia).16 The questionnaire was first written in English, then translated into Amharic and back to English by linguistic experts, and was tested prior to use. Additional details about data collection methods and study procedures have been previously described.15 All study participants provided informed consent, and all research protocols were approved by the institutional review boards of Addis Continental Institute of Public Health, Addis Ababa, Ethiopia, and the Human Subjects Division at the University of Washington, Seattle, Washington. The Harvard School of Public Health Office of Human Research Administration granted approval to use the de-identified dataset for analysis.
Definition of MetS and its components
MetS was defined using the International Diabetes Federation criteria,17 which is 1 of the 2 most widely used definitions of MetS. According to the International Diabetes Federation criteria, participants were considered to have MetS if they had abdominal obesity (defined as waist circumference of ≥94cm for men and ≥80cm for women) plus 2 of any of the following risk factors: (i) elevated triglycerides (≥150mg/dl) or specific treatment for this lipid abnormality; (ii) reduced HDL-C (<40mg/dl in men and <50mg/dL in women) or specific pharmacological treatment for this lipid abnormality; (iii) elevated BP (systolic BP ≥130 or diastolic BP ≥85mm Hg) or pharmacological treatment of previously diagnosed hypertension; (iv) impaired fasting serum glucose (≥100mg/dl) or previously diagnosed with type 2 diabetes.
Waist circumference was measured using a fixed tension tape at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest.13 BP from nondominant arm (typically left) was digitally measured (Microlife BP A50; Microlife AG, Widnau, Switzerland) after individuals had been sitting and resting for 5 minutes with legs uncrossed. Two additional BP measurements were taken with 3 minutes elapsing between successive measurements.15 Serum triglyceride concentrations were determined by standardized enzymatic procedures using glycerol phosphate oxidase assay. HDL-C was measured using the Ultra HDL assay, which is a homogeneous method for directly measuring HDL-C concentrations in serum or plasma without the need for off-line pretreatment or centrifugation steps. Participants’ fasting serum glucose was determined using the standardized glucose oxidase method. All laboratory assays were completed without knowledge of participants’ medical history at the International Clinical Laboratory in Addis Ababa, Ethiopia. The International Clinical Laboratory is one of the best-equipped laboratories in Ethiopia with internationally accredited standard operating procedures. Lipid, lipoprotein, and fasting serum glucose were reported as milligrams per deciliter.15
Definition of physical activity and covariables
Physical activity was defined as activity done by muscles in a systematic, structured, and repetitive manner to maintain body fitness. Physical activity was assessed using the previously validated Global Physical Activity Questionnaire. The Global Physical Activity Questionnaire has been widely used globally, including in sub-Saharan African countries.18 In accordance with the WHO, metabolic equivalent (MET)—which is the ratio of the work metabolic rate to the resting metabolic rate—was used to assess physical activity. One MET is defined as 1 kcal/kg/hour and is equivalent to the energy cost of sitting quietly, around 3.5ml/kg/min.19 A categorical indicator variable was created to define physical activity in 3 levels: (i) high: defined as a person reaching a vigorous-intensity activity on at least 3 days achieving a minimum of at least 25 MET hours/week or ≥7 days of any of the combination of walking, moderate- or vigorous-intensity activities achieving a minimum of at least 50 MET hours per week; (ii) moderate: defined as a person not meeting the criteria above but meeting ≥3 days of vigorous-intensity activity of at least 20 minutes per day or ≥5 days of moderate-intensity activity or walking for at least 30 minutes per day or ≥5 days of any of the combination of walking, moderate- or vigorous-intensity activities achieving a minimum of at least 10 MET hours per week; (iii) low: defined as a person not meeting any of the above criteria.20 Covariables included in the analysis were age, alcohol consumption (<1, 1–4, 5–6, 7 consumption days per week), khat chewing (yes, no), smoking status (current, former, never) and education (≤high school, technical school, ≥bachelor’s degree level).
Statistical analysis
Percentage was used to express the frequency distributions of categorical sociodemographic, lifestyle, and clinical variables. Mean ± standard deviation (SD) was provided for continuous variables, and Student t tests were used to evaluate the differences in mean for study groups. Because previous studies have noted that the effect of physical activity on MetS differs among men and women, analyses were reported for men and women separately.21 Chi-square tests were used to evaluate the differences in the distribution of the categorical variables stratified by sex. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) adjusted for age, smoking, alcohol intake, khat consumption, and educational status. All reported P values are 2-sided, and statistical significance was set at α = 0.05. Analyses were conducted using SAS for UNIX statistical analysis software (version 9.1.3; SAS Institute, Cary, NC).
RESULTS
Sociodemographic, lifestyle, and clinical characteristics of study participants according to MetS status stratified by sex are summarized in Table 1. Men with MetS (n = 160) were more likely to be previous or current smokers and khat users and were more likely to consume greater amounts of alcohol than those without MetS (n = 957). Overall, women (n = 726) were less likely to be smokers and were less likely to consume khat and alcohol than men. However, no statistically significant differences in the frequencies of smoking, khat, or alcohol consumption were observed among women with and without MetS. Participants with MetS from both sexes had significantly higher abdominal obesity, raised serum triglycerides, reduced HDL-C, and raised BP compared with without MetS.
Table 1.
Characteristics of study population by metabolic syndrome status
| Metabolic syndrome | ||||||
|---|---|---|---|---|---|---|
| Men | Women | |||||
| Characteristics | Yes | No | Pa | Yes | No | Pa |
| No. | 160 | 957 | 153 | 573 | ||
| Mean age, years (SD) | 46.55 (0.77) | 34.31 (0.36) | <0.01 | 45.9 (0.74) | 33.0 (0.44) | <0.01 |
| Education, % | 0.11 | 0.99 | ||||
| ≤12 years (high school) | 9.6 | 5.5 | 12.9 | 12.9 | ||
| 12–14 years (technical school) | 13.9 | 15.8 | 29.5 | 29.5 | ||
| ≥14 years (bachelors) | 76.5 | 78.7 | 57.7 | 57.6 | ||
| Smoking status, % | <0.01 | 0.52 | ||||
| Never smoker | 70.5 | 80.1 | 98.8 | 99.3 | ||
| Previous smoker | 23.5 | 12.6 | 1.2 | 0.5 | ||
| Current smoker | 6.0 | 7.3 | 0.0 | 0.2 | ||
| Alcohol intake, % | <0.01 | 0.4 | ||||
| Less than once a month | 49.2 | 68.2 | 92.4 | 96.3 | ||
| 1–4 days/week | 42.4 | 27.6 | 5.7 | 2.6 | ||
| 5–6 days/week | 3.8 | 2.6 | 1.0 | 0.6 | ||
| Daily | 4.6 | 1.6 | 1.0 | 0.6 | ||
| Khat intake, % | 0.59 | 0.93 | ||||
| No | 84.9 | 86.5 | 99.4 | 99.3 | ||
| Yes | 15.1 | 13.5 | 0.6 | 0.7 | ||
| Physical activity, % | 0.09 | 0.44 | ||||
| Low | 23.8 | 18.7 | 32.3 | 37.5 | ||
| Moderate | 42.1 | 38.5 | 37.3 | 33 | ||
| High | 34.2 | 42.8 | 30.4 | 29.6 | ||
| Waist circumference ≥94cm (men) or >80cm (women), % | 99.3 | 13.4 | <0.01 | 99.4 | 36.0 | <0.01 |
| Serum triglycerides ≥150mg/dl, % | 83.8 | 22.3 | <0.01 | 47.7 | 5.6 | <0.01 |
| Serum HDL cholesterol <40mg/dl (men) or <50mg/dl (women), % | 26.3 | 11.2 | <0.01 | 85.6 | 49.2 | <0.01 |
| Blood pressure (SBP ≥130mm Hg or DBP >85mm Hg), % | 80.6 | 30.8 | <0.01 | 68.0 | 12.9 | <0.01 |
| Fasting blood glucose ≥100mg/dl, % | 53.1 | 24.7 | <0.01 | 60.8 | 20.6 | <0.01 |
Abbreviations: DBP, diastolic blood pressure; SBP, systolic blood pressure.
aχ2 test P value.
Table 2 summarizes the independent association of the 3 levels of physical activity (low (reference), moderate, and high) with MetS. We observed an inverse linear trend in odds of MetS with increasing levels of physical activity in men (P trend = 0.02) but not in women (P trend = 0.85). Among men, the OR of MetS classified as being habitually engaged in high levels of physical activity, as compared with those classified as being engaged in low levels of activity, was 0.56 (95% CI = 0.33–0.97) after adjusting for age, smoking, educational status, and alcohol and khat consumption. We observed no evidence of an association of physical activity with MetS among women.
Table 2.
Prevalence of metabolic syndrome in men and women by increasing levels of physical activity
| Physical activity | ||||
|---|---|---|---|---|
| Group | Low | Moderate | High | P Value |
| Men | ||||
| Median (MET minutes/week) | 360 | 1200 | 5160 | |
| No. | 224 | 417 | 476 | |
| Age-adjusted model OR (95% CI) | 1.00 | 0.87 (0.54–1.38) | 0.70 (0.43–1.12) | 0.13 |
| Multivariable-adjusted model OR (95% CI)a | 1.00 | 0.95 (0.56–1.61) | 0.56 (0.33–0.97) | 0.02 |
| Women | ||||
| Median (MET minutes/week) | 320 | 1120 | 5360 | |
| No. | 269 | 237 | 220 | |
| Age-adjusted model OR (95% CI) | 1.00 | 1.01 (0.62–1.64) | 0.91 (0.55–1.51) | 0.73 |
| Multivariable-adjusted model OR (95% CI)a | 1.00 | 0.98 (0.52–1.83) | 1.07 (0.57–2.01) | 0.85 |
Abbreviations: CI, confidence interval; MET, metabolic equivalent; OR, odds ratio.
aMultivariable model adjusted for age, smoking, alcohol intake, khat intake, and educational status.
Table 3 summarizes the prevalence of each of the criteria for MetS by increasing levels of physical activity after adjusting for the confounding variables and stratified by sex. Physical activity was statistically significantly and inversely associated with high waist circumference (Ptrend = 0.01) and hypertriglyceridemia (Ptrend = 0.03) among men, but no such associations were observed among women. The OR of having high waist circumference comparing those with high to low levels of physical activity was 0.52 (95% CI = 0.33–0.82) among men. In addition, the OR of hypertriglyceridemia comparing those with high to low levels of physical activity was 0.64 (95% CI = 0.42–0.95) among men.
Table 3.
Prevalence of each of the criteria for metabolic syndrome in men and women by increasing levels of physical activity
| Men | Women | |
|---|---|---|
| Physical activity | ORa (95% CI) | ORa (95% CI) |
| Obese (waist circumference ≥94cm) | Obese (waist circumference >80cm) | |
| Low | 1.00 | 1.00 |
| Medium | 1.03 (0.66–1.61) | 0.83 (0.48–1.46) |
| High | 0.52 (0.33–0.82) | 0.67 (0.38–1.19) |
| P value for trend | <0.01 | 0.17 |
| Raised TG (serum TG ≥150mg/dl) | Raised TG (serum TG ≥150mg/dl) | |
| Low | 1.00 | 1.00 |
| Medium | 0.80 (0.53–1.21) | 1.00 (0.50–1.99) |
| High | 0.64 (0.42–0.95) | 0.88 (0.44–1.79) |
| P value for trend | 0.03 | 0.74 |
| Low HDL-C (serum HDL-C <40mg/dl) | Low HDL-C (serum HDL-C <50mg/dl) | |
| Low | 1.00 | 1.00 |
| Medium | 0.98 (0.57–1.68) | 1.69 (0.97–2.96) |
| High | 0.90 (0.53–1.53) | 1.22 (0.68–2.19) |
| P value for trend | 0.67 | 0.78 |
| High BP (systolic BP ≥130mm Hg) | High BP (systolic BP ≥130mm Hg) | |
| Low | 1.00 | 1.00 |
| Medium | 0.80 (0.53–1.21) | 0.77 (0.43–1.36) |
| High | 0.72 (0.48–1.08) | 0.88 (0.50–1.56) |
| P value for trend | 0.12 | 0.62 |
| Raised FBG (fasting glucose ≥100mg/dl) | Raised FBG (fasting glucose ≥100mg/dl) | |
| Low | 1.00 | 1.00 |
| Medium | 1.00 (0.65–1.52) | 0.76 (0.43–1.32) |
| High | 0.86 (0.57–1.30) | 0.97 (0.56–1.68) |
| P value for trend | 0.4 | 0.87 |
Abbreviations: BP, blood pressure; CI, confidence interval; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; OR, odds ratio; TG, triglycerides.
aMultivariable model adjusted for age, smoking, alcohol intake, khat intake, and educational status.
DISCUSSION
To the best of our knowledge, this is the first study to evaluate physical activity and MetS among Ethiopian adults. The results of this study confirm and expand the limited body of epidemiologic evidence among sub-Saharan Africans. Overall, higher levels of physical activity were inversely associated with MetS among Ethiopian men. In addition, higher levels of physical activity were inversely associated with abdominal obesity, and elevated triglycerides were inversely associated with higher levels of physical activity among men. No similar trends were observed among women in this cohort, in part because of the small sample size.
Overall, our findings among Ethiopian men are similar to those reported by investigators who have examined other populations.22–24 In a study of rural Cameroonians, investigators reported that regular physical activity that was roughly equivalent to 30min/day of brisk walking was associated with a lower prevalence of MetS.22 Other studies conducted in low-, middle-, and high-income countries have also documented inverse associations of MetS with increasing levels of physical activity or measures indicative of cardio-respiratory fitness.23–25 Carroll and colleagues, for instance, reported that higher levels of physical activity were associated with reductions in myriad cardiometabolic risk factors among participants in the British Regional Heart Study.23
Our findings documenting sex difference in the MetS and physical activity are in agreement with those reported by others.26,27 The explanation for these findings is uncertain, but we speculate physical activity (low, moderate, high) may not be well measured among women in this population. For example, Ethiopian women who are typically involved in daily living activities might have higher METs levels that are not captured in an instrument that more heavily favors assessment of leisure time physical activity. Finally, there could be underlying biological differences in MetS risk among men and women that requires further study.
Our results are also generally consistent with a number of experimental studies that have documented diverse metabolic benefits of physical activity. Halverstadt and colleagues reported that 24 weeks of endurance exercise training induced favorable changes in plasma lipoprotein and lipid profile independent of diet and baseline or change in body fat. For example, with exercise training, mean serum triglyceride concentrations decreased significantly (−17mg/dl; P < 0.001).28 Additionally, a randomized, controlled trial conducted by Kraus and colleagues among sedentary and overweight men and women with dyslipidemia reported that the highest amount of weekly exercise with minimal weight change had beneficial effects on the lipoprotein profiles.29
Several important limitations must be considered when interpreting the results of our study. First, because the study population was comprised of highly educated, middle-aged, white-collar employees, the results may not be generalizable to the entire Ethiopian population. Second, we used self-reported physical activity to classify study participants. Therefore, we cannot exclude the possibility that some misclassification may have occurred. Further, because of this cross-sectional data collection design, we cannot be certain of the temporal relation between level of physical activity and risk of MetS. Inferences concerning the protective or beneficial effects of physical activity on MetS and its components, however, will be enhanced with data from prospective studies that include objectively measured physical activity and randomized clinical trials conducted in this study population. Larger studies that allow for more careful characterization of physical activity (e.g., intensity, frequency, and type) and those that identify barriers to a more active lifestyle will be needed to help develop multilevel interventions for NCD prevention and health promotion in low-income sub-Saharan African countries.
In conclusion, our study findings suggest favorable effects of physical activity on the odds of MetS among Ethiopian men in an occupational cohort. The associations observed among Ethiopian men are consistent with the evidence documenting cardiovascular health benefits of a physically active lifestyle. Our study now provides the basis for designing lifestyle intervention studies directed toward Ethiopian men. For example, our findings suggest that men who expend at least 25 MET hours/week (equivalent to ≥7 days of walking, moderate- or vigorous-intensity activities achieving ≥50 MET hours/week or ≥ 3 days of vigorous-intensity activity achieving ≥25 MET hours/week) may substantially reduce their risk of MetS. Ethiopia, like other sub-Saharan African countries, is undergoing an epidemiological and nutritional transition where lifestyle and behavioral changes that promote physical inactivity, increased adult weight gain, and a clustering of cardiometabolic risk factors is common.30 Health promotion and NCD prevention programs designed to mitigate the adverse health effects of this epidemiological and nutritional transition are needed. Efforts to increase physical activity will be one important component of a comprehensive global public health effort aimed toward reducing the risks of NCDs in this population.
DISCLOSURE
The authors declared no conflict of interest.
ACKNOWLEDGMENTS
This research was supported by awards from the National Institutes of Health (National Institute on Minority Health and Health Disparities: T37-MD001449; and National Center for Research Resources and the National Center for Advancing Translational Sciences: 8UL1TR000170-05). The authors would like to thank International Clinical Laboratories for completing all laboratory analyses.
REFERENCES
- 1. Tunstall-Pedoe H. Preventing chronic diseases. A vital investment: WHO global report. World Health Organization: Geneva, Switzerland: 2005. [Google Scholar]
- 2. Yach D, Hawkes C, Gould CL, Hofman KJ. The global burden of chronic diseases. JAMA 2004; 291: 2616–2622 [DOI] [PubMed] [Google Scholar]
- 3. Yusuf S, Reddy S, Ounpuu S, Anand S. Global burden of cardiovascular diseases. Circulation 2001; 104: 2855–2864 [DOI] [PubMed] [Google Scholar]
- 4. Murray CJL, Lopez AD. Alternative projections of mortality and disability by cause 1990–2020: Global Burden of Disease Study. Lancet 1997; 349: 1498–1504 [DOI] [PubMed] [Google Scholar]
- 5. Teklu B. Disease patterns among civil servants in Addis Ababa: an analysis of out-patient visits to a bank employees’ clinic. Ethiopian Med J 1980; 18: 1 [PubMed] [Google Scholar]
- 6. Teklu B. Chronic disease prevalence in Ethiopian bank employees. Ethiopian Med J 1982; 20: 49 [PubMed] [Google Scholar]
- 7. Forrest KYZ, Bunker CH, Kriska AM, Ukoli FAM, Huston SL, Markovic N. Physical activity and cardiovascular risk factors in a developing population. Med Sci Sports Exerc 2001; 33: 1598 [DOI] [PubMed] [Google Scholar]
- 8. Pate RR, Pratt M, Blair SN, Haskell WL, Macera CA, Bouchard C, Buchner D, Ettinger W, Heath GW, King AC. Physical activity and public health. JAMA 1995; 273: 402–407 [DOI] [PubMed] [Google Scholar]
- 9. United States Public Health Service, Office of the Surgeon General, President’s Council on Physical Fitness and Sports Physical activity and health: report of the Surgeon General. US Government Printing Office: Washington, DC: 1998. [Google Scholar]
- 10. Kelliny C, William J, Riesen W, Paccaud F, Bovet P. Metabolic syndrome according to different definitions in a rapidly developing country of the African region. Cardiovasc Diabetol 2008; 7: 27 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012; 380: 219–229 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Chase NL, Sui X, Lee D, Blair SN. The association of cardiorespiratory fitness and physical activity with incidence of hypertension in men. Am J Hypertens 2009; 22: 417–424 [DOI] [PubMed] [Google Scholar]
- 13. WHO Chronic diseases and health promotion: stepwise approach to surveillance (STEPS). World Health Organization: Geneva, Switzerland: 2010. [Google Scholar]
- 14. WHO Primary health care management of trachoma. World Health Organization: Geneva, Switzerland: 1993. [Google Scholar]
- 15. Wai WS, Dhami RS, Gelaye B, Girma B, Lemma S, Berhane Y, Bekele T, Khali A, Williams MA. Comparison of measures of adiposity in identifying cardiovascular disease risk among Ethiopian adults. Obesity 2012; 20: 1887–1895 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Getahun W, Gedif T, Tesfaye F. Regular khat (Catha edulis) chewing is associated with elevated diastolic blood pressure among adults in Butajira, Ethiopia: a comparative study. BMC Public Health 2010; 10: 390 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Alberti KG, Zimmet P, Shaw J. The metabolic syndrome—a new worldwide definition. Lancet 2005; 366: 1059 [DOI] [PubMed] [Google Scholar]
- 18. Guthold R, Louazani SA, Riley LM, Cowan MJ, Bovet P, Damasceno A, Sambo BH, Tesfaye F, Armstrong TP. Physical activity in 22 African countries: results from the World Health Organization STEPwise approach to chronic disease risk factor surveillance. Am J Prev Med 2011; 41: 52–60 [DOI] [PubMed] [Google Scholar]
- 19. Howley ET. Type of activity: resistance, aerobic and leisure versus occupational physical activity. Med Sci Sports Exerc 2001; 33: S364–S369; discussion S419–S420 [DOI] [PubMed] [Google Scholar]
- 20. WHO Global physical activity surveillance. World Health Organization: Geneva, Switzerland: 2009. [Google Scholar]
- 21. Wilmore JH. Dose-response: variation with age, sex, and health status. Med Sci Sports Exerc 2001; 33: S622 [DOI] [PubMed] [Google Scholar]
- 22. Assah FK, Ekelund U, Brage S, Mbanya JC, Wareham NJ. Urbanization, physical activity, and metabolic health in sub-saharan Africa. Diabetes Care 2011; 34: 491–496 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Carroll S, Cooke CB. Metabolic clustering, physical activity and fitness in nonsmoking, middle-aged men. Med Sci Sports Exerc 2000; 32: 2079 [DOI] [PubMed] [Google Scholar]
- 24. Godsland IF, Leyva F, Walton C, Worthington M, Stevenson JC. Associations of smoking, alcohol and physical activity with risk factors for coronary heart disease and diabetes risk in the first follow-up cohort of the Heart Disease and Diabetes Risk Indicators in a Screened Cohort study (HDDRISC-1). J Intern Med 1998; 243: 33–41 [DOI] [PubMed] [Google Scholar]
- 25. Torjesen PA, Birkeland KI, Anderssen SA, Hjermann I, Holme I, Urdal P. Lifestyle changes may reverse development of the insulin resistance syndrome. The Oslo Diet and Exercise Study: a randomized trial. Diabetes Care 1997; 20: 26–31 [DOI] [PubMed] [Google Scholar]
- 26. Regitz-Zagrosek V, Lehmkuhl E, Weickert MO. Gender differences in the metabolic syndrome and their role for cardiovascular disease. Clin Res Cardiol 2006; 95: 136–147 [DOI] [PubMed] [Google Scholar]
- 27. Rhodes RE, Mark RS, Temmel CP. Adult sedentary behavior: a systematic review. Am J Prev Med 2012; 42: e3–e28 [DOI] [PubMed] [Google Scholar]
- 28. Halverstadt A, Phares DA, Wilund KR, Goldberg AP, Hagberg JM. Endurance exercise training raises high-density lipoprotein cholesterol and lowers small low-density lipoprotein and very low-density lipoprotein independent of body fat phenotypes in older men and women. Metabolism 2007; 56: 444–450 [DOI] [PubMed] [Google Scholar]
- 29. Kraus WE, Houmard JA, Duscha BD, Knetzger KJ, Wharton MB, McCartney JS, Bales CW, Henes S, Samsa GP, Otvos JD, Kulkarni KR, Slentz CA. Effects of the amount and intensity of exercise on plasma lipoproteins. N Engl J Med 2002; 347: 1483–1492 [DOI] [PubMed] [Google Scholar]
- 30. Tran A, Gelaye B, Girma B, Lemma S, Berhane Y, Bekele T, Khali A, Williams MA. Prevalence of metabolic syndrome among working adults in Ethiopia. Int J Hypertens 2011; 2011: 193719 [DOI] [PMC free article] [PubMed] [Google Scholar]