iron , an essential component in human tissue , plays a crucial role in transporting oxygen in the body as well as in cellular processes including dna , rna , and protein synthesis .
hemoglobin , an oxygen - carrying protein in red blood cells , accounts for about two - thirds of body s iron supply . about 10% of essential iron contributes to the formation of myoglobin , cytochrome , iron - containing enzymes .
recently , attention has been paid to iron overload , which is the opposite problem of iron deficiency , in developed countries .
iron overload is characterized by the excessive accumulation of iron in the body , which is known as hemochromatosis .
it is defined as serum ferritin levels > 400 ng / ml for men and > 300 ng / ml for women or as transferrin saturation ( tsat ) levels > 50% for men and
it has been suggested that excess amount of free iron in the body cause the formation of oxygen radicals leading to peroxidative damages to vital cell structures . in fact , it was reported that iron overload was associated with increased risks of liver disease , diabetes mellitus , cardiovascular disease , and parkinson s and alzheimer s diseases .
data on the association between lifestyle factors , such as alcohol consumption , smoking , physical activity , and iron overload are still limited and inconsistent .
alcohol consumption tends to increase iron absorption by down - regulating hepcidin , which is a major regulator of iron homeostasis , and may lead to iron accumulation in the body .
however , epidemiological data on the alcohol consumption and iron overload in general populations are limited .
one study reported no difference in plasma iron levels between non - smokers and smokers .
but , another study examined that pregnant women who had smoked had higher ferritin levels in blood than those who had never smoked .
this discrepancy may be due to the use of different iron biomarkers ; ferritin and tsat are better indicators of iron status than iron in serum or plasma . in terms of the link between physical activity and iron status , some studies reported that ferritin and transferrin levels in blood were elevated after treadmill running test .
limitations of these previous studies on the association between lifestyle factors and iron overload include a small sample size and a lack of generalizability .
in addition , to the best of our knowledge , there is no study to examine joint effects of lifestyle factors on iron overload . in present study ,
we investigated on the associations of smoking status , alcohol consumption , and physical activity with iron overload , which was defined by tsat levels .
furthermore , we conducted joint analysis of smoking status and alcohol consumption in the association with iron overload .
we carried out a cross - sectional study embedded in a population - based cohort study , which is an ongoing longitudinal investigation .
the study participants were 2,347 korean aged 4979 years who completed the follow - up interview of the cohort study between february 2011 and november 2012 and provided blood samples for assays of iron status biomarkers . in the questionnaire - based interview , they provided informationon socio - demographics , lifestyle factors , health status , and medical history .
they singed an informed consent form approved by the human subjects review committee at the korea university ansan hospital .
after excluding participants who reported diagnosis of cancer , diabetes mellitus , and hypertension or who showed iron deficiency ( tsat levels < 15% ) or who had missing values of lifestyle factors were excluded .
serum samples were collected and delivered to the seoul clinical laboratories ( seoul , korea ) for assays of iron , ferritin , and unsaturated iron - binding capacity ( uibc ) , which was used to calculate total iron - binding capacity ( tibc ) and tsat .
tibc was obtained by adding serum iron and uibc concentrations , and tsat was calculated by multiplying the ratio of serum iron and tibc by 100 . regarding assay methods , colorimetry for iron and uibc and immunoassays for ferritin
applicable assay kits were purchased from siemens ( tarrytown , ny , usa ) and nittobo ( osaka , japan ) .
information on lifestyle factors such as smoking status , alcohol consumption , and physical activity levels was collected .
anthropometric measurement was conducted by a trained researcher . according to a standardized protocol , height ( cm ) and body weight ( kg )
were measured to the nearest 0.1 cm or 0.1 kg , respectively , without footwear , and body mass index ( bmi , kg / m ) was calculated .
information on smoking status ( never / former smoker / current smoker ) and the number of cigarettes smoked was obtained .
information on the average frequency of alcohol drinking occasions , the amount of alcohol consumed on a typical occasion , and the volume of one standard drink for each alcoholic beverage was obtained , and the daily amount of alcohol consumed ( g / day ) was calculated .
participants were also asked to complete a table that inquired about alcohol drinking amount and pattern in the past 30 days .
thus , we collected information on average frequency of drinking occasion , amount of 6 types of alcoholic beverage ( beer , wine , hard liquor , and 3 types of traditional drinks , including soju , chungju , and makgeolli ) consumed for a typical occasion , and the volume of 1 standard drink for each type of alcoholic beverage .
we calculated beverage - specific alcohol consumption in g / day on the basis of the alcohol content ( 4.5% for beer , 12% for wine , 40% for hard liquor , 22% or 25% for soju , 16% for chungju , and 6% for makgeolli ) , the frequency of drinking , and the amount consumed .
we calculated total alcohol consumption ( g / day ) by summing up the beverage - specific amount consumed as well as total liquor consumption ( g / day ) by summing up the alcohol amount from liquor , including hard liquor , soju , and chungju .
information on physical activity level was obtained using five categories for activity intensity with open - ended questions about the hours spent in a typical day per level of intensity .
a total metabolic equivalent score ( met ) was calculated by multiplying the hours spent at a particular activity intensity by its met values ( 1.0 for sleep or sedentary , 1.5 for very light activity , 2.4 for light activity , 5.0 for moderate activity , and 7.5 for vigorous activity ) , which were determined based on examples of activities given for each category .
confounding variables such as age , sex , and the presence of hypertension or diabetes mellitus were collected .
the presence of hypertension was confirmed by using antihypertensive medications or having systolic blood pressure ( bp ) of  140 mmhg or diastolic bp of  90 mmhg .
bp was measured in a sitting position using a mercury sphygmomanometer after a rest period of at least 5 minutes .
repeated bp measurements were performed at approximately 30-second intervals and recorded to the nearest 2 mmhg .
the average of two measurements each in the left and right arms was calculated for systolic and diastolic bp .
the presence of diabetes mellitus was confirmed if the following criteria were met : fasting plasma glucose level of  126 mg / dl or postprandial glucose level of  200 mg / dl or use of medications for diabetes mellitus . according to the quartiles of tsat levels , descriptive statistics for demographic and clinical characteristics , information on lifestyle factors , and blood assay results of the study participants
the anova test was used to assess differences in means across the quartiles of tsat levels . for categorical data ,
a chi - square test was used to assess differences in proportions across the quartiles of tsat levels .
to analyze associations between iron overload and lifestyle factors , we conducted multivariate logistic regression analysis and obtained odds ratio ( or ) and 95% confidence interval ( ci ) . in the multivariate models , covariates including age ( continuous ) , sex , bmi ( continuous ) , smoking status ( categories : nonsmoking , former smoking , current smoking of 110 cigarettes / day , or current smoking of > 10 cigarettes / day ) , alcohol consumption ( categories : nondrinking , alcohol consumption of 114.9 g / day , 1530 g / day , or > 30 g / day ) , met for physical activity ( continuous ) , the presence of hypertension or diabetes mellitus ( binary ) were included .
we also performed stratified analysis by sex and joint analysis of smoking status and alcohol consumption in the association with iron overload .
all statistical analyses were performed with the sas version 9.4 software ( sas institute , cary , nc , usa ) .
we carried out a cross - sectional study embedded in a population - based cohort study , which is an ongoing longitudinal investigation .
the study participants were 2,347 korean aged 4979 years who completed the follow - up interview of the cohort study between february 2011 and november 2012 and provided blood samples for assays of iron status biomarkers . in the questionnaire - based interview , they provided informationon socio - demographics , lifestyle factors , health status , and medical history .
they singed an informed consent form approved by the human subjects review committee at the korea university ansan hospital .
after excluding participants who reported diagnosis of cancer , diabetes mellitus , and hypertension or who showed iron deficiency ( tsat levels < 15% ) or who had missing values of lifestyle factors were excluded .
serum samples were collected and delivered to the seoul clinical laboratories ( seoul , korea ) for assays of iron , ferritin , and unsaturated iron - binding capacity ( uibc ) , which was used to calculate total iron - binding capacity ( tibc ) and tsat .
tibc was obtained by adding serum iron and uibc concentrations , and tsat was calculated by multiplying the ratio of serum iron and tibc by 100 . regarding assay methods , colorimetry for iron and uibc and immunoassays for ferritin
applicable assay kits were purchased from siemens ( tarrytown , ny , usa ) and nittobo ( osaka , japan ) .
information on lifestyle factors such as smoking status , alcohol consumption , and physical activity levels was collected .
anthropometric measurement was conducted by a trained researcher . according to a standardized protocol , height ( cm ) and body weight ( kg )
were measured to the nearest 0.1 cm or 0.1 kg , respectively , without footwear , and body mass index ( bmi , kg / m ) was calculated .
information on smoking status ( never / former smoker / current smoker ) and the number of cigarettes smoked was obtained .
information on the average frequency of alcohol drinking occasions , the amount of alcohol consumed on a typical occasion , and the volume of one standard drink for each alcoholic beverage was obtained , and the daily amount of alcohol consumed ( g / day ) was calculated .
participants were also asked to complete a table that inquired about alcohol drinking amount and pattern in the past 30 days .
thus , we collected information on average frequency of drinking occasion , amount of 6 types of alcoholic beverage ( beer , wine , hard liquor , and 3 types of traditional drinks , including soju , chungju , and makgeolli ) consumed for a typical occasion , and the volume of 1 standard drink for each type of alcoholic beverage .
we calculated beverage - specific alcohol consumption in g / day on the basis of the alcohol content ( 4.5% for beer , 12% for wine , 40% for hard liquor , 22% or 25% for soju , 16% for chungju , and 6% for makgeolli ) , the frequency of drinking , and the amount consumed .
we calculated total alcohol consumption ( g / day ) by summing up the beverage - specific amount consumed as well as total liquor consumption ( g / day ) by summing up the alcohol amount from liquor , including hard liquor , soju , and chungju .
information on physical activity level was obtained using five categories for activity intensity with open - ended questions about the hours spent in a typical day per level of intensity .
a total metabolic equivalent score ( met ) was calculated by multiplying the hours spent at a particular activity intensity by its met values ( 1.0 for sleep or sedentary , 1.5 for very light activity , 2.4 for light activity , 5.0 for moderate activity , and 7.5 for vigorous activity ) , which were determined based on examples of activities given for each category .
confounding variables such as age , sex , and the presence of hypertension or diabetes mellitus were collected .
the presence of hypertension was confirmed by using antihypertensive medications or having systolic blood pressure ( bp ) of  140 mmhg or diastolic bp of  90 mmhg .
bp was measured in a sitting position using a mercury sphygmomanometer after a rest period of at least 5 minutes .
repeated bp measurements were performed at approximately 30-second intervals and recorded to the nearest 2 mmhg .
the average of two measurements each in the left and right arms was calculated for systolic and diastolic bp .
the presence of diabetes mellitus was confirmed if the following criteria were met : fasting plasma glucose level of  126 mg / dl or postprandial glucose level of  200 mg / dl or use of medications for diabetes mellitus .
according to the quartiles of tsat levels , descriptive statistics for demographic and clinical characteristics , information on lifestyle factors , and blood assay results of the study participants were calculated . for continuous data ,
the anova test was used to assess differences in means across the quartiles of tsat levels . for categorical data ,
a chi - square test was used to assess differences in proportions across the quartiles of tsat levels .
to analyze associations between iron overload and lifestyle factors , we conducted multivariate logistic regression analysis and obtained odds ratio ( or ) and 95% confidence interval ( ci ) . in the multivariate models , covariates including age ( continuous ) , sex , bmi ( continuous ) , smoking status ( categories : nonsmoking , former smoking , current smoking of 110 cigarettes / day , or current smoking of > 10 cigarettes / day ) , alcohol consumption ( categories : nondrinking , alcohol consumption of 114.9 g / day , 1530 g / day , or > 30 g / day ) , met for physical activity ( continuous ) , the presence of hypertension or diabetes mellitus ( binary ) were included .
we also performed stratified analysis by sex and joint analysis of smoking status and alcohol consumption in the association with iron overload .
all statistical analyses were performed with the sas version 9.4 software ( sas institute , cary , nc , usa ) .
this cross - sectional study included 1,118 ( 56.7% ) men and 855 women ( 43.3% ) . among them , 288 ( 25.8% )
table 1 shows descriptive statistics on lifestyle factors , confounding variables , and iron biomarkers according to the quartiles of tsat levels .
participants with higher tsat levels were more likely to be younger ( p < 0.01 ) , men , smokers , and alcohol drinkers ( p < 0.001 ) and less likely to have hypertension ( p < 0.01 )
bmi , body mass index ; met , total metabolic equivalent score ; tibc , total iron binding capacity ; tsat , transferrin saturation . 

table 2 presents results for the associations between iron overload and lifestyle factors in all participants .
heavy alcohol drinkers had 1.6-fold higher or ( 95% ci , 1.112.36 ) of iron overload than non - drinkers .
heavy smokers were likely to have a higher or than never - smokers ( p = 0.07 ) . or , odds ratio ; ci , confidence interval ; met , total metabolic equivalent score . 

data are adjusted for age , sex , body mass index , smoking status , alcohol consumption , physical activity , and the presence of hypertension or diabetes mellitus .
next , we evaluated associations stratified by sex between lifestyle factors and iron overload ( table 3 ) . in men , heavy alcohol drinkers had 1.7-fold higher or ( 95% ci , 1.132.56 ) of iron overload than non - drinkers while heavy smoking tended to increase or ( p = 0.19 ) . in women ,
former or current smokers had 1.9-fold higher or ( 95% ci , 1.013.63 ) of iron overload than never - smokers while moderate or heavy alcohol consumption tended to increase or ( p = 0.62 ) . or , odds ratio ; ci , confidence interval ; met , total metabolic equivalent score . 

data are adjusted for age , body mass index , smoking status , alcohol consumption , physical activity , and the presence of hypertension or diabetes mellitus . 

table 4 presents results for the association iron overload in joint analysis of smoking status and alcohol consumption .
compared with non - smokers who abstained from alcohol consumption , smokers with > 10 cigarettes / day who consumed alcohol > 15 g / day had a 2.6-fold higher or ( 95% ci , 1.235.61 ) and any smokers with heavy alcohol consumption > 30 g / day had higher ors between 2 and 3 for iron overload . or , odds ratio ; ci , confidence interval . 

data are adjusted for age , sex , body mass index , smoking status , alcohol consumption , physical activity , and the presence of hypertension or diabetes mellitus .
in a population - based cross - sectional study , we observed positive associations of alcohol consumption and smoking status with iron overload . in particular , the association for alcohol consumption was significant only among men while that for smoking was only among women
in addition , heavy smokers were more likely to have iron overload even if they had moderate alcohol consumption with 15 to 30 g / day .
heavy alcohol drinkers with > 30 g / day were more likely to have iron overload even if they were former smokers or moderate smokers with < 10 cigarettes / day .
serum tsat levels indicates the proportion of iron - binding sites of transferrin loaded with iron and has been used as a sensitive biomarker of iron status than serum iron or tibc .
its level is determined by sex , race , iron consumption , and the presence of infection or metabolic diseases as well as by genetic factors .
its normal values range between 15% and 40% approximately and thus tsat levels > 50% for men or > 45% for women
iron overload with tsat levels > 50% may lead to the accumulation of non - transferrin - bound iron or labile iron , which is involved in the production of reactive oxygen species ( ros ) via the fenton reaction or the haber - weiss reaction .
alcohol - induced disorders with abnormal iron metabolism have been investigated in animal models as well as in clinical and epidemiological studies .
it was reported that patients with alcoholic liver disease are likely to have increased iron stores , as reflected by elevated serum iron biomarkers such as tsat or ferritin .
a potential biological mechanism underlying these observations is that alcohol may be implicated in the regulation of hepcidin expression in the liver .
hepcidin is a key regulator of iron status by controlling iron absorption in the intestine .
reduced hepcidin concentrations by down - regulation of hepcidin expression allow intestinal absorption of iron leading to the elevation of circulating iron as well as iron storage .
it was reported that alcohol consumption down - regulates hepcidin expression in a vitro study with hepatoma cells as well as in a vivo study with mice exposed to alcohol .
hepcidin concentrations decreased after drinking alcohol and then iron absorption increased with promoting ferroportin as a corridor in the gastrointestinal cells and membrane of macrophage .
prior studies have examined elevated iron concentrations in smokers . as a potential biological mechanism , it has been suggested that smoking may stimulate erythropoiesis in a dose - related manner due to hypoxia , which is induced by smoking .
physical activity , especially intense physical activity , may cause a number of unfavorable changes , including an increase in the level of pro - inflammatory cytokines and decreased iron absorption .
one study showed that a high - intensity exercise test caused significant changes in hepcidin levels , interleukin-6 , and iron metabolism during the recovery period .
another study observed that serum iron levels decreased significantly during the recovery period after exercise .
the strengths of our study include a large sample size , investigation in a general population , consideration of a variety of lifestyle factors , and presentation of joint effects of lifestyle factors in the association with iron overload .
study limitations should be taken into account for the interpretation of our findings . because the study design was cross - sectional ,
because the findings may be generalizable to middle - aged and older asians , further studies for other age groups or other ethnicities are warranted . in this cross - sectional study
, we observed that heavy alcohol drinking and smoking are positively associated with iron overload . on the basis of the findings , heavy alcohol drinking and smoking may need to be avoided to prevent iron accumulation in the body
 it has been suggested that iron overload , which indicates the accumulation of iron , generates cellular reactive oxygens and causes peroxide damages to the body . 
 such oxidative stresses , in a broader context , are also caused by lifestyles such as alcohol consumption and smoking . 
 however , there are limited data on the association between these lifestyle factors and internal iron overload . in present study 
 , we evaluated associations between lifestyle factors , such as smoking status , alcohol consumption , and physical activity , and serum markers of iron overload . in a population - based cross - sectional study including 2,347 korean men and women aged 4979 years , we assessed serum transferrin saturation ( tsat ) levels and defined iron overload as tsat levels > 50% for men and > 45% for women . after excluding persons with chronic diseases and iron deficiency , multivariate odds ratio ( or ) and its 95% confidence interval ( ci ) 
 were estimated to evaluate associations between lifestyle factors and iron overload in 1,973 participants . in all participants 
 , we examined a significantly positive association between heavy alcohol consumption ( > 30 g / day ) and iron overload ; heavy drinkers showed 1.6-fold higher or ( 95% ci , 1.112.36 ) than non - drinkers . 
 stratified analysis by sex showed that this association was significant only among men . 
 in addition , we observed a potential association between heavy smoking > 10 cigarettes / day and iron overload ( p = 0.07 ) . 
 in stratified analysis by sex , we examined a significant association between smoking and iron overload only among women ; former or current smokers had 1.9-fold higher or ( 95% ci , 1.013.63 ) than never - smoker . 
 our findings suggest that heavy alcohol consumption and smoking may worsen iron accumulation in the body . 
INTRODUCTION
MATERIALS AND METHODS
Study population
Blood collection and assessments
Lifestyle factors and other confounding variables
Statistical analysis
RESULTS
DISCUSSION