participants for this study were recruited from two urban areas ( yaound , the capital city of cameroon , and bamenda , the capital city of the north western region ) and two rural areas ( mbankomo and bafut ) of cameroon .
the inhabitants of the urban sites are mainly middle - class public or private sector workers or businessmen .
residential houses in the urban areas are grouped closely together and arranged in blocks with paved or graded road access . in the rural areas ,
the rural habitation pattern is sparse , with most of the homes and farms accessed only via foot paths . as a result of the absence of complete population registers ,
a sampling frame was established following enumeration of eligible adults in houses in delimited areas of the study sites .
eligible participants were adults aged between 25 and 55 years without previously diagnosed diabetes or any known cardiovascular disease .
all 3,854 eligible participants ( rural : n = 2,238 , mean age 35.3  7.7 years ; urban : n = 1,616 , mean age 35.4  8.3 years ) in the sampling frame were approached through door - to - door recruitment and invited to participate in the study . a total of 651 volunteers ( rural : n = 303 , mean age 38.5  8.3 years ; urban : n = 348 , mean age 37.9  9.1 years ) took part in this study .
volunteers were provided detailed information about the study verbally and in writing , and invited to attend a testing session at their local hospital .
volunteers were asked to refrain from eating , drinking or smoking starting at 10:00 p.m. the evening prior to testing .
personal and sociodemographic data , as well as data on smoking , alcohol consumption , and fruit and vegetable intake were collected by self - report using an adapted world health organization ( who ) stepwise approach to sureveillance questionnaire .
ethical approval for the study was obtained from the cameroon national ethics committee , and all participants provided signed informed consent .
pregnant women and other volunteers who could not take part in exercise testing according to study protocol were excluded from the study .
an exercise screening questionnaire , adapted from the who rose angina questionnaire was used to screen for preexisting cardiovascular disease which would contraindicate exercise testing .
free - living physical activity was measured using a combined heart rate ( hr ) and movement sensor ( actiheart ; cambridge neurotechnology , cambridge , u.k . ) which has been validated in this population in free - living adults with doubly labeled water method as criterion ( 14 ) .
the individual hr response to the mechanical work during an 8-min incremental step test was used for individual calibration of hr data ( 15 ) . during the test
, hr was monitored in real time and the test was aborted if hr reached 90% of the age - predicted maximum hr ( 16 ) , if the subject could not keep up with the stepping protocol , or if they requested to stop .
free - living physical activity was measured in 1-min epochs using the combined hr and movement sensor over 7 continuous days .
the participants were requested to carry on with their normal habitual lifestyle and wear the monitor at all times except while showering , bathing , or swimming .
participants with less than 2 full days of free - living data ( n = 51 ) were not included in these analyses .
hr data were preprocessed ( 17 ) and converted to energy expenditure using the individual calibration derived from the step test , and the accelerometer data were converted to energy expenditure using group acceleration equations corresponding to level walking or running ( 15 ) .
minute - by - minute hr and movement - derived physical activity intensity was combined in a branched equation model ( 18 ) to calculate free - living paee
. basal metabolic rate ( ~resting energy expenditure [ ree ] ) was estimated using the oxford equations ( 19 ) , and total energy expenditure ( tee ) was calculated by adding ree and a component for the thermic effect of food ( equivalent to 10% of tee ) to the derived paee .
energy expenditure variables are expressed per kilogram body weight to adjust for differences in body size .
the distribution of intensity of activity was expressed as average daily time ( min / day ) spent at 1 met equal to time spent asleep or sedentary , between 1 and 3 mets equal to light physical activity , above 3 mets equal to moderate - to - vigorous physical activity .
an estimate of cardiorespiratory fitness ( vo2max in ml of o2/kg / min ) was calculated as the intensity of work at the age - predicted maximum heart rate ( 15 ) by extrapolation of the individual heart rate response to mechanical work derived from the step test calibration .
body weight was measured using electronic clinical scales , and body composition was measured using bio - impedance ( tanita tbf-531 scales ; tanita uk , uxbridge , middlesex , u.k . ) .
bmi was calculated as the ratio of body weight ( kg ) to the square of height ( m ) and categorized as normal : < 25 ; overweight : 25 to < 30 ; and obese : 30
waist circumference was measured at the level of the midpoint between the lower costal margin and the anterior superior iliac crests .
measurement was made to the nearest 0.1 cm using a nonstretch fiberglass tape measure with participants wearing light indoor clothing .
central obesity was defined as waist circumference 80 cm in women or 94 cm in men , or using the cut points of the national cholesterol education program - adult treatment panel iii ( ncep - atp iii ) ( 20 ) when included to define the metabolic syndrome .
measurements were made on the dominant arm after 5 min of rest with the subject seated .
three measurements were taken at 1-min intervals , and the average of the three constituted the final blood pressure value .
capillary blood glucose readings were measured after an overnight fast of at least 8 h , and then 2 h after ingestion of 75 g of glucose dissolved in 300 ml of water .
blood glucose measurements were done on whole fresh capillary blood using a hemocue b - glucose analyzer ( hemocue ab , ngelholm , sweden ) .
the metabolic syndrome was defined using the ncep - atp iii criteria ( 20 ) . to demonstrate the population distribution of global metabolic health
, we computed a continuous summary metabolic risk score ( z - score ) largely on the basis of the components of the metabolic syndrome .
this variable was derived by standardizing and then summing waist circumference , blood pressure ( average of systolic and diastolic ) , blood glucose ( average of fasting , 30-min , and 2-h glucose ) , triglycerides , body fat , fasting insulin , and inverse hdl cholesterol .
the standardization of these continuous variables was computed by subtracting the sample mean from the individual value and then dividing by the sd of the sample mean .
sex - specific calculations were made for waist circumference , body fat , fasting insulin , and hdl cholesterol .
fasting blood samples were collected in the mornings between 7:30 and 9:30 a.m. plasma and serum samples were separated upon collection in a refrigerated centrifuge at 4c .
samples were transported on dry ice by air to cambridge ( u.k . ) and stored at 80c until further analyses .
assays were performed by the national institute for health research cambridge biomedical research centre , core biochemical assay laboratory .
hdl cholesterol and triglycerides were measured using automated assays on the dade behring dimension rxl analyzer ( siemens healthcare , camberley , u.k . ) .
hdl was measured using a homogenous accelerator selective detergent assay and triglycerides were measured using an enzymatic assay according to manufacturers specifications .
ldl was calculated by the friedwald formula ( ldl = cholesterol  hdl  [ triglycerides/2.2 ] ) .
fasting insulin was assayed in singleton on a 1235 autodelfia automatic immunoassay system using a two - step time resolved fluorometric assay kit manufactured by perkin elmer life sciences ( wallac oy , turku , finland ) .
pmol / l , 3233 split proinsulin 1% at 2,800 pmol / l , and c - peptide < 0.1% at 5,280
analyses were carried out using stata version 10.1 ( statacorp , college station , tx ) .
descriptive characteristics of the study sample are presented as means with sd , adjusted means with se , or as numbers with proportions , stratified by sex - specific paee quartiles . for dichotomous grouping variables ,
difference in means was assessed using the student t test and difference in proportion using the  test or fisher exact test .
independent associations between paee and the metabolic syndrome were examined in multivariate logistic regression models .
there was no paee interaction by residential site or sex on its association with the metabolic syndrome .
models were either unadjusted or adjusted for age , sex , residential site , smoking , alcohol consumption , fruit and vegetable consumption , and educational level ( as a surrogate for socioeconomic status ) . to illustrate the population impact of physical inactivity on metabolic health
, we calculated the population attributable fraction of prevalent metabolic syndrome due to being in the lowest quartile of paee ( q1-paee ) .
the population attributable fraction was computed as = ( prevalence of q1-paee in case subjects  prevalence of q1-paee in control subjects)/(1  prevalence of q1-paee in control subjects ) .
free - living physical activity was measured using a combined heart rate ( hr ) and movement sensor ( actiheart ; cambridge neurotechnology , cambridge , u.k . ) which has been validated in this population in free - living adults with doubly labeled water method as criterion ( 14 ) .
the individual hr response to the mechanical work during an 8-min incremental step test was used for individual calibration of hr data ( 15 ) . during the test , hr was monitored in real time and the test was aborted if hr reached 90% of the age - predicted maximum hr ( 16 ) , if the subject could not keep up with the stepping protocol , or if they requested to stop .
free - living physical activity was measured in 1-min epochs using the combined hr and movement sensor over 7 continuous days .
the participants were requested to carry on with their normal habitual lifestyle and wear the monitor at all times except while showering , bathing , or swimming .
participants with less than 2 full days of free - living data ( n = 51 ) were not included in these analyses .
hr data were preprocessed ( 17 ) and converted to energy expenditure using the individual calibration derived from the step test , and the accelerometer data were converted to energy expenditure using group acceleration equations corresponding to level walking or running ( 15 ) .
minute - by - minute hr and movement - derived physical activity intensity was combined in a branched equation model ( 18 ) to calculate free - living paee .
basal metabolic rate ( ~resting energy expenditure [ ree ] ) was estimated using the oxford equations ( 19 ) , and total energy expenditure ( tee ) was calculated by adding ree and a component for the thermic effect of food ( equivalent to 10% of tee ) to the derived paee .
energy expenditure variables are expressed per kilogram body weight to adjust for differences in body size .
the distribution of intensity of activity was expressed as average daily time ( min / day ) spent at 1 met equal to time spent asleep or sedentary , between 1 and 3 mets equal to light physical activity , above 3 mets equal to moderate - to - vigorous physical activity .
an estimate of cardiorespiratory fitness ( vo2max in ml of o2/kg / min ) was calculated as the intensity of work at the age - predicted maximum heart rate ( 15 ) by extrapolation of the individual heart rate response to mechanical work derived from the step test calibration .
body weight was measured using electronic clinical scales , and body composition was measured using bio - impedance ( tanita tbf-531 scales ; tanita uk , uxbridge , middlesex , u.k . ) .
bmi was calculated as the ratio of body weight ( kg ) to the square of height ( m ) and categorized as normal : < 25 ; overweight : 25 to < 30 ; and obese : 30
waist circumference was measured at the level of the midpoint between the lower costal margin and the anterior superior iliac crests .
measurement was made to the nearest 0.1 cm using a nonstretch fiberglass tape measure with participants wearing light indoor clothing .
central obesity was defined as waist circumference 80 cm in women or 94 cm in men , or using the cut points of the national cholesterol education program - adult treatment panel iii ( ncep - atp iii ) ( 20 ) when included to define the metabolic syndrome .
measurements were made on the dominant arm after 5 min of rest with the subject seated .
three measurements were taken at 1-min intervals , and the average of the three constituted the final blood pressure value .
capillary blood glucose readings were measured after an overnight fast of at least 8 h , and then 2 h after ingestion of 75 g of glucose dissolved in 300 ml of water .
blood glucose measurements were done on whole fresh capillary blood using a hemocue b - glucose analyzer ( hemocue ab , ngelholm , sweden ) .
the metabolic syndrome was defined using the ncep - atp iii criteria ( 20 ) . to demonstrate the population distribution of global metabolic health
, we computed a continuous summary metabolic risk score ( z - score ) largely on the basis of the components of the metabolic syndrome .
this variable was derived by standardizing and then summing waist circumference , blood pressure ( average of systolic and diastolic ) , blood glucose ( average of fasting , 30-min , and 2-h glucose ) , triglycerides , body fat , fasting insulin , and inverse hdl cholesterol .
the standardization of these continuous variables was computed by subtracting the sample mean from the individual value and then dividing by the sd of the sample mean .
sex - specific calculations were made for waist circumference , body fat , fasting insulin , and hdl cholesterol .
fasting blood samples were collected in the mornings between 7:30 and 9:30 a.m. plasma and serum samples were separated upon collection in a refrigerated centrifuge at 4c .
samples were transported on dry ice by air to cambridge ( u.k . ) and stored at 80c until further analyses .
assays were performed by the national institute for health research cambridge biomedical research centre , core biochemical assay laboratory .
hdl cholesterol and triglycerides were measured using automated assays on the dade behring dimension rxl analyzer ( siemens healthcare , camberley , u.k . ) .
hdl was measured using a homogenous accelerator selective detergent assay and triglycerides were measured using an enzymatic assay according to manufacturers specifications .
ldl was calculated by the friedwald formula ( ldl = cholesterol  hdl  [ triglycerides/2.2 ] ) .
fasting insulin was assayed in singleton on a 1235 autodelfia automatic immunoassay system using a two - step time resolved fluorometric assay kit manufactured by perkin elmer life sciences ( wallac oy , turku , finland ) .
pmol / l , 3233 split proinsulin 1% at 2,800 pmol / l , and c - peptide < 0.1% at 5,280
analyses were carried out using stata version 10.1 ( statacorp , college station , tx ) .
descriptive characteristics of the study sample are presented as means with sd , adjusted means with se , or as numbers with proportions , stratified by sex - specific paee quartiles . for dichotomous grouping variables ,
difference in means was assessed using the student t test and difference in proportion using the  test or fisher exact test .
independent associations between paee and the metabolic syndrome were examined in multivariate logistic regression models .
there was no paee interaction by residential site or sex on its association with the metabolic syndrome .
models were either unadjusted or adjusted for age , sex , residential site , smoking , alcohol consumption , fruit and vegetable consumption , and educational level ( as a surrogate for socioeconomic status ) . to illustrate the population impact of physical inactivity on metabolic health
, we calculated the population attributable fraction of prevalent metabolic syndrome due to being in the lowest quartile of paee ( q1-paee ) .
the population attributable fraction was computed as = ( prevalence of q1-paee in case subjects  prevalence of q1-paee in control subjects)/(1  prevalence of q1-paee in control subjects ) .
descriptive characteristics of the study sample stratified by sex and rural or urban residence are presented in supplementary table 1 .
clinical and metabolic characteristics of the study sample stratified by sex - specific quartiles of paee are presented in table 1 .
most of the individual metabolic and clinical parameters , as well as the clustered metabolic risk score or prevalence of the metabolic syndrome showed a significant linear trend across quartiles of paee .
blood lipids were generally low in this sample with no sex or rural - urban differences .
prevalence of metabolic syndrome was almost fourfold lower in the highest compared with the lowest quartile of paee .
clinical and metabolic characteristics by quartiles of paee in adult cameroonians ( n = 552 ) data are age - adjusted means  se or n ( % ) .
bg , blood glucose ; bp , blood pressure ; ms , metabolic syndrome ; wc , waist circumference ; zms , clustered metabolic risk score .
urban dwellers had a significantly lower paee than rural dwellers ( 44.2  21.0 vs. 59.6  23.7 kj / kg / day , p < 0.001 ) and a higher prevalence of the metabolic syndrome ( 17.7 vs. 3.5% , p < 0.001 ) ( supplementary tables 1 and 2 ) .
there was no significant difference between the sexes in metabolic risk expressed as a continuous clustered metabolic score , but urban dwellers had a significantly higher mean score than rural dwellers ( 0.80  3.67 vs. 1.11  2.90 , p < 0.001 ) .
this difference was observed to correspond to a rural - to - urban right shift in the population density distribution of the clustered metabolic z - score when stratified by residential area ( fig .
a similar but reverse difference was observed with the population distribution of paee , with a rural - to - urban left shift in the distribution .
population distribution of paee and clustered metabolic z - score in adults in rural and urban cameroon .
table 2 presents independent associations between paee quartiles and prevalent metabolic syndrome . with the lowest quartile of paee as reference
, there was a strong inverse association between paee and prevalent metabolic syndrome . compared with the lowest quartile of paee , being in the 2nd quartile of paee
was associated with a reduction in the risk of prevalent metabolic syndrome , which was not statistically significant ( odds ratio 0.63 [ 95% ci 0.321.25 ] ) .
the risk of prevalent metabolic syndrome was significantly lower for the 3rd and 4th quartiles of paee compared with the 1st quartile ( 0.32 [ 0.14  0.73 ] and 0.19 [ 0.08  0.49 ] , respectively ) .
multivariate adjustments for age , sex , residential area , smoking , alcohol drinking , fruit and vegetable consumption , and educational level as potential confounders attenuated but did not change these associations .
independent associations between paee and metabolic syndrome in adult cameroonians ( n = 552 ) data are odds ratio or odds ratio ( 95% ci ) .
adjusted for age , sex , residential area , smoking , alcohol consumption , fruit and vegetable consumption , and number of years of education . defining the lowest quartile of paee to represent sedentary or inactive lifestyle ,
the population attributable fraction of prevalent metabolic syndrome due to a sedentary or inactive lifestyle was 26.3% ( 25.3% in women and 35.7% in men ) . expressing paee as a continuous variable , and assuming a linear relationship with the metabolic syndrome , each
kj / kg / day of paee was associated with a 2.1% lower risk of prevalent metabolic syndrome ( odds ratio 0.98 , p = 0.03 ) , after adjustment for potential confounders as in table 2 , model 3 .
this implies that an increase of 6.5 kj / kg / day of paee would correspond to approximately 13.7% risk reduction in prevalent metabolic syndrome .
this amount of paee can be achieved by 30 min / day of brisk walking .
our results suggest that free - living paee was significantly and independently associated with prevalent metabolic syndrome .
this association persisted after multivariate adjustments for possible confounders and was similar in both urban and rural dwellers , even though rural dwellers were more physically active and had a more favorable metabolic profile than urban dwellers .
low levels of physical activity may be contributing significantly to the metabolic syndrome in this population .
theoretically , these data suggest a 26.3% population attributable fraction of prevalent metabolic syndrome as a result of being in the lowest quartile of paee .
however , independent of several confounders , it is likely that small changes in paee may confer significant benefits in terms of lower risk of metabolic syndrome .
because of the cross - sectional design of our study , we can not infer causality .
the study sample included only adults aged 2555 years without known metabolic syndrome or cvd .
therefore , these results may not be directly generalizable to younger or older individuals , as well as individuals with diagnosed prevalent metabolic or cardiovascular disease .
the lack of complete population registers as well as the absence of fixed house addresses or telephone numbers limited our ability to use simple random sampling of participants .
our use of volunteers from a study - established sampling frame may introduce sampling bias , which would limit the generalizability of these results even to our target population .
however , our sample was similar to other larger population - based surveys with respect to bmi , blood pressure , and educational level ( 21,22 ) .
separate from prevalence of risk factors , one could argue that educational level may have influenced volunteering for this study .
however , the proportion of volunteers in this sample having at least a secondary education ( 44% of men and 35% of women ) was comparable to data from the 2004 demographic and health survey in cameroon ( 48% of men and 32% of women ) ( 21 ) .
the observed inverse association between total volume of physical activity ( paee ) with the metabolic syndrome is comparable to results from previous studies which used objective measures of physical activity ( 12,13,23 )
( 23 ) reported a significant inverse association between paee scaled for fat - free body mass and a clustered metabolic syndrome score .
however , we scaled paee for body weight , not fat - free mass . although researchers agree that paee should be expressed taking into account differences in body size , the exact scaling factor applicable to body size is still a contentious issue . during light intensity locomotion activities , which are the main component of total activity in many people ,
the expression of paee per kilogram body weight may be more appropriate for the habitual free - living activity pattern , and is easy to interpret for clinical or public health usage .
the importance of the distribution of free - living physical activity intensities , beyond total volume of physical activity , on metabolic health is still uncertain .
many studies that have examined the effect of intensity distribution of physical activity on global metabolic risk have used self - report of physical activity ( 24 ) .
studies that have used objective assessment of physical activity intensity distribution are less common ( 12,13 ) .
most studies confirm the deleterious effect of increasing sedentary time or decreasing moderate - to - vigorous physical activity on the metabolic syndrome ( 12,24 ) .
however , the benefits of increasing overall activity compared with shifting the intensity distribution toward more vigorous activity is still inconclusive . in this study
we show that objectively measured total volume of physical activity had a significant independent association with the metabolic syndrome
. our use of total volume of activity may be more applicable to health promotion initiatives in regions with low literacy .
it may be more feasible to encourage overall physical activity than to recommend specific subdimensions of activity to less educated people .
rapid urbanization of lifestyle in sub - saharan africa is characterized by increasing prevalence and clustering of metabolic risk factors such as diabetes , high blood pressure , and obesity ( 4,25 ) .
our data show an evident rural - urban gradient of paee , which mirrors progression toward western levels of habitual physical activity . this transition is not only explained by increasing frequency of high risk individuals , but by a shift in the underlying population distribution of risk factors .
our use of an aggregate variable for metabolic health ( the metabolic syndrome ) is relevant for assessing the effects of physical activity level on multiple risk factors in the whole population .
further , the metabolic syndrome is associated with a higher morbidity and mortality ( 3 ) .
we did not collect data on energy intake in this study because of the difficulties of collecting objective dietary data in a population - based study .
however , we adjusted for self - reported fruit and vegetable intake in the analyses , which would capture part of the variance associated with healthy or unhealthy dietary habits .
these data suggest a significant population burden of prevalent metabolic syndrome associated with being in the lowest quartile of paee , or a mean paee of 26  7
this level of physical activity corresponds to an average of 45 met - hours / week .
typically , these individuals would be spending more than 80% of their time in sedentary activities with very little physical effort . encouraging people to increase their physical activity , even through reduction of sedentary time , may confer considerable health benefits especially in the least active individuals . in conclusion ,
reduction in physically active lifestyles as a result of urbanization may be critical in driving the current transition toward a higher burden of metabolic diseases in this region .
public health interventions to increase physical activity may be expected to significantly curb the burden of metabolic syndrome in sub - saharan africa .
 objectivewe examined the independent associations between objectively measured free - living physical activity energy expenditure ( paee ) and the metabolic syndrome in adults in rural and urban cameroon.research design and methodspaee was measured in 552 rural and urban dwellers using combined heart rate and movement sensing over 7 continuous days . 
 the metabolic syndrome was defined using the national cholesterol education program - adult treatment panel iii criteria.resultsurban dwellers had a significantly lower paee than rural dwellers ( 44.2  21.0 vs. 59.6  23.7 kj / kg / day , p < 0.001 ) and a higher prevalence of the metabolic syndrome ( 17.7 vs. 3.5% , p < 0.001 ) . in multivariate regression models adjusted for possible confounders , each kj / kg / day of paee was associated with a 2.1% lower risk of prevalent metabolic syndrome ( odds ratio 0.98 , p = 0.03 ) . 
 this implies a 6.5 kj / kg / day difference in paee , equivalent to 30 min / day of brisk walking , corresponds to a 13.7% lower risk of prevalent metabolic syndrome . 
 the population attributable fraction of prevalent metabolic syndrome due to being in the lowest quartile of paee was 26.3% ( 25.3% in women and 35.7% in men).conclusionsurban compared with rural residence is associated with lower paee and higher prevalence of metabolic syndrome . 
 paee is strongly independently associated with prevalent metabolic syndrome in adult cameroonians . 
 modest population - wide changes in paee may have significant benefits in terms of reducing the emerging burden of metabolic diseases in sub - saharan africa . 
RESEARCH DESIGN AND METHODS
Physical activity measurement
Anthropometry and clinical measures
Metabolic syndrome and clustered metabolic risk score
Biochemical assays
Calculations and statistical analyses
RESULTS
CONCLUSIONS