Association of Smoking and Alcohol Consumption with the Presence of Sarcopenia at Follow-up in Community-Dwelling People Aged 40–74 Years
Article information
Abstract
Background
Evidence on the association of smoking and drinking with sarcopenia is scarce. This study aimed to examine the association between smoking levels/alcohol consumption and sarcopenia in community-dwelling middle-aged and older adults.
Methods
This study consisted of 6,654 community-dwelling residents aged 40–74 years (mean age: 62.4 years, 54.8% women). At the baseline survey (2011–2014), demographic information, lifestyle habits (including smoking levels and alcohol consumption), physical characteristics, and medical history were obtained. Follow-up physical examinations were conducted in 2021 and 2022. Sarcopenia was diagnosed using modified the Asian Working Group for Sarcopenia 2019 criteria, with low muscle mass defined as the sex-specific 20th percentile of appendicular lean mass (ALM)/height².
Results
Sarcopenia was present in 272/6,654 cases (4.1%). Smoking levels were associated with higher odds of the presence of sarcopenia at follow-up (adjusted p for trend=0.0367), with the ≥20-cigarettes/day group having a higher OR than non-smokers (adjusted odds ratio [OR]=1.95, 95% confidence interval [CI] 1.17–3.24). Drinking levels were associated with lower odds of the presence of sarcopenia in women (adjusted p for trend=0.0013), but not in men (adjusted p for trend=0.9872). A subgroup analysis showed that smoking ≥20 cigarettes/day was associated with higher odds of the presence of sarcopenia than non-smoking (adjusted OR=2.14, 95% CI 1.13–4.04) in drinkers, but not in non-drinkers (p for interaction between levels of smoking and alcohol consumption=0.0483).
Conclusion
Higher smoking levels were associated with sarcopenia, particularly among individuals who smoked ≥20 cigarettes/day, and an interaction between smoking and alcohol consumption was suggested. However, caution is warranted in interpreting causality, as this study did not assess sarcopenia at baseline.
INTRODUCTION
Sarcopenia is an age-related musculoskeletal disorder characterized by a progressive decline in muscle mass and strength.1) It can adversely affect health through muscle weakness, increased risk of falls, reduced physical function, disability, and frailty, primarily due to inflammation and hormonal changes.2,3) Although its prevalence varies depending on the diagnostic criteria used and population studied, it reportedly ranges from 1% to 29% among community-dwelling older adults.4) The economic burden associated with sarcopenia is also substantial. In the United States, the annual healthcare costs attributable to this condition are estimated at $18.5 billion, and a 10% reduction in its prevalence could result in an annual healthcare cost saving of approximately $1.1 billion.5) Given these considerations, sarcopenia prevention should be recognized as a public health priority in aging societies.
Smoking and alcohol consumption are major lifestyle factors that influence health and reportedly have a negative impact on the development of sarcopenia. Smoking-induced oxidative stress and inflammation may contribute to muscle loss through pathways involving myostatin, impaired muscle protein synthesis, and other catabolic mechanisms.6) A meta-analysis reported higher odds of smoking for sarcopenia (odds ratio [OR]=1.12) compared to non-smoking.7) More recently, a cohort study reported that smokers were 2.4 times more likely to develop sarcopenia compared to non-smokers.8) Furthermore, a recent cross-sectional study reported that smokers had a 1.8-fold higher risk of sarcopenia compared to non-smokers.9) However, a dose-dependent relationship between the number of cigarettes smoked and sarcopenia has not been established.7-9) In addition, most previous studies were cross-sectional, highlighting the need for large-scale longitudinal studies.
The association between alcohol consumption and sarcopenia is complex. A meta-analysis involving 62 observational studies (60 were cross-sectional studies) revealed no linear association between alcohol consumption and sarcopenia; rather, a nonlinear (J-shaped) relationship was observed.10) A UK Biobank study suggested that high alcohol consumption has a harmful effect on the development of sarcopenia based on a cross-sectional analysis, but found no association between alcohol consumption and developing sarcopenia in a follow-up analysis.11) Similar to studies on smoking, few longitudinal studies have addressed this topic and with inconsistent findings. Furthermore, smoking and heavy alcohol consumption cause oxidative stress in humans, and their interactive effects on numerous chronic diseases have been suggested.12) In this context, their interaction may also contribute to sarcopenia.
This study aimed to examine associations of smoking levels and alcohol consumption with sarcopenia among middle-aged and older adults, and to explore potential interactions between smoking and alcohol consumption on the risk of sarcopenia. While many previous studies on sarcopenia have focused on older individuals, the present study targeted people in earlier life stages, i.e., between the ages of 40 and 74 years, potentially providing insights into modifiable factors for the early prevention of sarcopenia. This approach may also provide a life-course perspective on how pre-old-age lifestyle factors influence later muscle health.
MATERIALS AND METHODS
Design and Participants
This study examined the association between smoking levels and alcohol consumption at baseline (2011–2014) and the presence of sarcopenia at follow-up physical examinations conducted in 2021 and 2022. Participants were selected from individuals who participated in the baseline surveys of the Murakami Cohort Study (n=14,364)13) and the Uonuma Cohort Study (n=30,707).14) All eligible participants for the physical examinations were invited by mail—12,246 from the Murakami cohort and 21,534 from the Uonuma cohort. Of these, 2,199 individuals from the Murakami cohort and 4,772 from the Uonuma cohort, totaling 6,971 participants, took part in the physical examinations. The participant selection process is illustrated in Fig. 1. The following participants were excluded from the statistical analysis: 124 individuals with missing handgrip strength data; 87 individuals with asymmetrical appendicular skeletal muscle mass values considered outliers, possibly due to hemiplegia or residual metal implants; and 10 individuals with outlier values for appendicular skeletal muscle mass. We further excluded participants with exclusively high or low body mass index (BMI) or energy intake (n=88), as well as those with multiple missing values (n=8), leaving 6,654 participants (3,005 men and 3,649 women) for the final analysis population.
Since this study was based on a subset of the original cohort, we compared the baseline characteristics of the analytic sample with those of the entire cohort. Baseline percent distributions of age, sex, smoking, and alcohol consumption in the present sample (n=6,654) and the original total sample (45,071) are summarized in Supplementary Table S1.
Written informed consent was obtained from all participants, and the study protocol was approved by the Niigata University Ethics Committee (Approval Nos. 2019-0376, 2019-0409, and 2022-0240).
Baseline Survey (2011–2014)
The baseline surveys were conducted from 2011 to 2013 for the Murakami cohort and from 2012 to 2014 for the Uonuma cohort. Self-administered questionnaires were used to collect data on demographics, lifestyle habits, physical characteristics, and medical history, including heart disease (myocardial infarction, angina, atrial fibrillation, and heart failure), stroke, and diabetes. For smoking, participants were asked whether they were current smokers, had smoked in the past, or had never smoked. Current smokers were further asked about the number of cigarettes they smoked daily. Smoking levels were classified into four categories: “non-smoker,” “past smoker,” “1–19 cigarettes/day,” and “≥20 cigarettes/day”.13,15)
For alcohol consumption, participants were asked whether they were current drinkers, had drunk in the past, or were non-drinkers. Those who reported drinking at least once a month were further asked about their drinking frequency (<1 day/month, 1–3 days/month, 1–2 days/week, 3–4 days/week, 5–6 days/week, and every day) and the quantity of alcohol consumed by type of beverage. The ethanol content (g) for each alcoholic drink was calculated as follows: 180 mL of sake (rice wine) was equivalent to 23 g of ethanol, 180 mL of shochu or awamori (white spirits) to 36 g, 30 mL of whiskey or brandy to 10 g, 60 mL of wine to 6 g, and 633 mL of beer to 23 g. Weekly ethanol intake was calculated by combining daily ethanol intake with drinking frequency, and participants were classified into six categories: “abstainer,” “past drinker,” “>0–149 g/week,” “150–299 g/week,” “300–449 g/week,” and “≥450 g/week”.15,16) The validity of alcohol consumption was assessed using 12-day dietary records. Spearman energy-adjusted correlation coefficients for alcohol consumption between the questionnaire and dietary records were 0.82 for men and 0.67 for women.17) The corresponding values for reproducibility were 0.84 for men and 0.80 for women.18)
Codes for marital status, educational background, and occupation are provided in Supplementary Table S2. Physical activity level was assessed using metabolic equivalent (MET) scores (MET-hours/day), which were calculated based on activity frequency and durations reported in the questionnaire.19) BMI was calculated by dividing weight (kg) by the square of height (m2), and energy intake was assessed using a validated food frequency questionnaire.17) Self-reported sleep duration was obtained based on the Pittsburgh Sleep Quality Index.20)
Physical Examinations (2021–2022)
Physical examinations were conducted in 2021 and 2022, coinciding with the annual health checkups organized by local governments. Body composition was assessed using multi-frequency bioelectrical impedance analysis (MF-BIA) with a stand-on 8-electrode MF-BIA device (MC-780A-N; Tanita, Tokyo, Japan). A high correlation has been reported between data obtained from this device and those from dual-energy X-ray absorptiometry (DXA).21) Grip strength was measured using a digital handgrip dynamometer (Grip-D, TKK-5401; Takei Scientific Instruments, Niigata, Japan), with two measurements taken for each hand while standing, and the maximum value was used. Sarcopenia diagnosis was based on the criteria of the Asian Working Group for Sarcopenia (AWGS) 2019,22) utilizing adjusted appendicular lean mass divided by height squared (ALM/ht2) and grip strength. However, the prevalence of sarcopenia was reported to be extremely low in Japanese data (particularly in women) using the AWGS 2019 criteria, possibly reflecting population-specific body composition, including a low BMI.23) Therefore, the 20th percentile value of ALM/ht2 was adopted as an alternative cutoff.23) Accordingly, the cutoff values for sarcopenia in the present study were set at ALM/ht2 <6.95 kg/m2 for men and <6.07 kg/m2 for women. The cutoff values for grip strength were set at <28 kg for men and <18 kg for women, based on the AWGS 2019 criteria.21)
Statistical Analysis
Statistical analyses were performed using SAS statistical software (Release 9.13; SAS Institute Inc., Cary, NC, USA). A total of 140 individuals had missing data for the following variables: BMI (n=19), education (n=108), physical activity (n=3), smoking (n=9), and alcohol consumption (n=1). For these cases, missing values were imputed using multiple imputation with PROC MI (NIMPUTE=3) in SAS, incorporating sex, age, education, marital status, occupation, log-transformed BMI, log-transformed energy intake, total physical activity, smoking, alcohol consumption, and histories of heart disease, stroke, and diabetes as covariates in the imputation model. Each imputed dataset was analyzed separately, and the estimates were combined using Rubin’s rules with PROC MIANALYZE. Imputed data were not used in analyses for which smoking (n=9) or drinking (n=1) was the outcome. For participant characteristics, continuous variables are presented as medians (interquartile ranges). p for trend values were calculated using ordinal logistic regression analysis. The outcome of this study was the presence or absence of sarcopenia at follow-up, with smoking levels and alcohol consumption as primary predictors. Odds ratios (ORs) for sarcopenia were calculated using simple and multiple logistic regression analyses. When conducting logistic regression analyses with smoking as the predictor, imputed smoking data were not used; the same approach was applied to alcohol consumption. Multivariable analyses included the following sarcopenia risk factors as covariates, based on a recent review article24): BMI,25) total physical activity level,26) alcohol consumption or smoking, extreme sleep duration (<6 hours or >8 hours, dummy variable),27) energy intake,24) and history (dummy variable) of heart disease24) stroke,28) and diabetes,29) as well as demographic factors including age, sex, marital status (dummy variable), education level, and occupation (dummy variable). To assess the robustness of the results, we conducted sensitivity analyses without imputation, using sarcopenia defined according to the original diagnostic criteria of AWGS 2019 as the outcome, and applying inverse-probability weighting to account for potential selection bias due to loss to follow-up, with participation probabilities estimated by logistic regression including baseline covariates. As a subgroup analysis, ORs for sarcopenia according to smoking levels were calculated for drinkers (alcohol consumption, >0 g ethanol/week) and non-drinkers (abstainers and past drinkers), and the interaction between smoking levels and alcohol consumption on sarcopenia was evaluated by calculating p for interaction values. We did not perform stratified analyses by smoking status because the proportion of smokers was small (13.6%). A p-value of <0.05 was considered statistically significant.
RESULTS
The mean age of participants was 62.4 years (standard deviation [SD]=7.1). Participant characteristics at baseline according to smoking levels and alcohol consumption are shown in Table 1, those according to levels of smoking and alcohol consumption by sex are shown in Supplementary Tables S3 and S4, and detailed information on marital status, education level, smoking, and alcohol consumption according to levels of smoking and alcohol consumption are shown in Supplementary Tables S5 and S6. At a mean of 9.1 years (SD=1.6) after baseline, the presence of sarcopenia was noted in 1/423 (0.2%) among participants in their 40s, 21/1,484 (1.4%) among those in their 50s, 133/3,635 (3.7%) among those in their 60s, 117/1,112 (10.5%) among those in their 70s, and 272/6,654 (4.1%) overall. Participant characteristics for the 2021–2022 physical examinations by sex are shown in Supplementary Table S7.
Participant characteristics at the 2011–2014 baseline survey according to levels of smoking and alcohol consumption
Higher smoking levels were associated with higher odds of the presence of sarcopenia at follow-up (multivariable-adjusted p for trend=0.0367), with the ≥20-cigarettes/day group having a higher OR than non-smokers (multivariable-adjusted OR=1.95, 95% confidence interval [CI] 1.17–3.24) (Table 2). When the ≥20-cigarettes/day group was subdivided into the 20-cigarettes/day group (23/365 cases) and the >20-cigarettes/day group (8/126 cases, median: 30 cigarettes/day), the respective multivariable-adjusted ORs were 1.86 (95% CI 1.07–3.23) and 2.29 (95% CI 0.99–5.28), with an overall multivariable-adjusted p for trend of 0.0213 (Fig. 2). A similar trend was observed (multivariable-adjusted p for trend=0.0397) in the male subgroup, with the ≥20-cigarettes/day group having significantly higher odds of the presence of sarcopenia than non-smokers (multivariable-adjusted OR=1.98, 95% CI 1.09–3.58) (Table 2). Although a statistically significant association was not observed in the female subgroup (multivariable-adjusted p for trend=0.5551), the ≥20-cigarettes/day group had significantly higher odds of the presence of sarcopenia than non-smokers (multivariable-adjusted OR=4.30, 95% CI 1.38–13.38). Sensitivity analyses for the association between smoking levels and odds of the presence of sarcopenia without imputation, using the original diagnostic criteria of AWGS 2019 and inverse-probability weighting, are shown in Table 3. The pattern of these associations was similar to that in Table 2.
Multivariable-adjusted odds ratios (ORs) for sarcopenia according to smoking levels, adjusted for sex, age, marital status, education, occupation, BMI, total physical activity, energy intake, alcohol consumption, extreme sleep duration, and histories of heart disease, stroke, and diabetes. The overall association was statistically significant (p for trend=0.0213), although the >20 cigarettes/day group did not reach statistical significance. Participants who smoked 20 or more cigarettes per day were divided into two subgroups according to the median. The numbers of participants were 3,786 for non-smokers, 1,952 for past smokers, 416 for the 1–19-cigarettes/day group, 365 for the 20-cigarettes/day group, and 126 for the >20-cigarettes/day group.
Sensitivity analyses of odds ratios (ORs) for the presence of sarcopenia at follow-up according to smoking levels
Significant associations were observed between alcohol consumption and odds of the presence of sarcopenia in the overall study population and women (multivariable-adjusted p for trend=0.0492 and 0.0013, respectively); however, no association was observed in men (multivariable-adjusted p for trend=0.9872) (Table 4). Sensitivity analyses for the association between drinking levels and the presence of sarcopenia without imputation, using the original diagnostic criteria of AWGS 2019 or inverse-probability weighting, are shown in Supplementary Table S8. The pattern of these associations was similar to that in Table 4.
Presence of sarcopenia at follow-up and odds ratios (ORs) according to alcohol consumption categories
The presence of sarcopenia and ORs according to smoking levels by drinking status are shown in Table 5. Smoking ≥20 cigarettes/day was associated with higher odds compared with non-smoking among drinkers (multivariable-adjusted OR=2.14, 95% CI 1.13–4.04), with a multivariable-adjusted p for trend of 0.0289, whereas no such association was observed among non-drinkers (multivariable-adjusted p for trend=0.7435). The p for interaction between levels of smoking and alcohol consumption on the multivariable-adjusted odds of the presence of sarcopenia was 0.0483.
DISCUSSION
The main findings of the present study were as follows: (1) smoking levels were associated with increased odds of the presence of sarcopenia at follow-up; in particular, individuals who smoked ≥20 cigarettes/day had the highest odds; (2) an inverse association was observed between alcohol consumption and the presence of sarcopenia in the overall population, but not among men; and (3) the association between smoking and the presence of sarcopenia may be stronger among individuals with higher alcohol consumption, suggesting an interaction between smoking and alcohol consumption.
Smoking levels were found to be associated with increased odds of the presence of sarcopenia, particularly among individuals who smoked ≥20 cigarettes/day compared to non-smokers, suggesting that there may be a dose-response relationship between smoking and sarcopenia (Fig. 2). However, the OR in the >20 cigarettes/day group was not statistically significant and should therefore be interpreted with caution. These findings imply that smoking during middle age and early older adulthood adversely affects the musculoskeletal system, leading to subsequent declines in muscle mass and muscle strength.
Previous studies have compared sarcopenia status between smokers and non-smokers. According to a meta-analysis of cross-sectional studies,7) smokers had a significantly higher prevalence of sarcopenia than non-smokers (OR=1.12). More recently, a longitudinal study8) reported that smokers had a higher risk of sarcopenia than non-smokers (risk ratio=2.36). These findings are consistent with another longitudinal study that assessed skeletal muscle strength, showing that smoking is associated with decreased muscle strength in adults.30) These two longitudinal studies suggest a causal association between smoking and the risk of sarcopenia.
A number of studies have proposed possible mechanisms underlying the association between smoking and the risk of sarcopenia. One study31) reported that smoking impairs muscle protein synthesis and upregulates the expression of genes associated with compromised muscle maintenance. Another study32) reported that serum cotinine levels were inversely associated with muscle mass. These findings suggest a causal link in which smoking increases the risk of sarcopenia.
In the sex-stratified analysis, we observed an association between smoking and the presence of sarcopenia in men, but not in women. The lack of a significant association in women may be attributable to insufficient statistical power due to the small number of female smokers. Nevertheless, this finding is consistent with previous evidence indicating that the smoking-related decline in both the quantity and quality of skeletal muscle is greater in men than in women.33,34)
We further examined the association between alcohol consumption and odds of the presence of sarcopenia, and an inverse association was observed in the overall study population, but not among men. A recent meta-analysis found no association between alcohol consumption and sarcopenia overall.10) Similarly, a longitudinal analysis (n=12,298) of the UK Biobank study showed no association between alcohol consumption and 4-year declines in muscle mass/strength.11) In addition, a cohort study among individuals aged ≥65 years reported no association between alcohol consumption and sarcopenia risk.35) The results in men in the present study are generally consistent with those of these previous studies.10,11,35) The overall association between alcohol consumption and sarcopenia was statistically significant; however, this result appears to have been largely driven by the findings in women, whose alcohol consumption was much lower than that of men. The prevalence of sarcopenia among women in groups consuming >300 g ethanol/week was zero, which may be explained by insufficient statistical power or the healthy drinker effect (i.e., healthier individuals may be more likely to continue drinking). In addition, the relatively high prevalence of sarcopenia among female abstainers and past drinkers may be due to the sick quitter effect (i.e., individuals with poorer health may be more likely to stop drinking).36) For these reasons, the results for the overall population do not necessarily provide clear evidence of a dose–response association between alcohol consumption and sarcopenia.
Our results suggest an interaction between smoking and alcohol consumption on the risk of sarcopenia. The mechanisms underlying the alcohol-smoke interaction on muscle health have not been fully elucidated; however, pharmacodynamic and behavioral interactions and additive effects on the antioxidant defense system may play a role. First, chronic consumption of alcohol may lead to an increase in the volume of distribution of nicotine due to the altered activity of cytochrome P450 families,37) which are known to be reduced in sarcopenic older individuals.38) Second, chronic exposure to a combination of ethanol and nicotine results in additive oxidative tissue injuries in rats.12) Third, smoking and alcohol have reciprocal reinforcing effects mediated by common dopaminergic reward pathways.39) Finally, both smoking and alcohol consumption may alter the gastrointestinal microbiome, resulting in dysbiosis associated with systemic inflammation and altered immune responses.40) Nonetheless, further studies will be needed to confirm our observations.
In the present study, younger individuals (<60 years), men, smokers, and heavy drinkers (≥450 g ethanol/week) tended not to participate in the follow-up physical examination (Supplementary Table S1). This may be partly due to the fact that the physical examination was commonly conducted in association with annual health checkups offered by the local government. Thus, individuals with greater health awareness, who are generally more likely to attend health checkups,41) may have been more likely to participate, potentially reducing the representativeness of the findings. Analysis of the overall association between smoking levels and sarcopenia using inverse-probability weighting showed a slightly lower OR (1.84) than that in the main analysis (OR=1.95). This suggests the possibility of a slight overestimation due to selection bias.
A strength of this study is that it provides important evidence on the association of smoking and alcohol consumption with sarcopenia in a large East Asian population. However, this study also has several limitations worth noting. First, sarcopenia status at baseline was not assessed, and some participants may already have had sarcopenia at the time of the baseline survey. Consequently, some cases identified at follow-up may not represent incident sarcopenia, raising the possibility of reverse causation or misclassification. Second, because deterioration in health status, including sarcopenia, may lead individuals to quit smoking or drinking,36,42) individuals with sarcopenia may have been more likely to be included in the smoking cessation and non-drinking groups in the present study, potentially resulting in an underestimation of the ORs for smoking and alcohol consumption. Third, lifestyle information was assessed using self-reported questionnaires, which may have led to misclassification and, consequently, an underestimation of ORs. Fourth, because abstainers were used as the reference group, this group may include individuals who abstain from alcohol due to health problems; therefore, the ORs should be interpreted with caution. Fifth, although we adjusted for energy intake, we did not consider other dietary factors, such as protein intake, as potential residual confounders. Finally, since BIA is influenced by an individual’s hydration status, it may have affected the assessment of muscle mass.
As with many other diseases, smoking has been shown to exert dose-dependent adverse effects on sarcopenia, providing further evidence in support of smoking cessation. With regard to alcohol consumption, no adverse effects on sarcopenia were observed. Nevertheless, in view of the numerous health risks inherent to alcohol, drinking cannot be regarded as a habitual practice for the prevention of sarcopenia.
In conclusion, the present study targeting middle-aged and older individuals demonstrated that smoking levels are positively associated with sarcopenia, particularly among individuals who smoked ≥20 cigarettes/day. Although a statistically significant association with sarcopenia was observed for alcohol consumption, the findings should be interpreted with caution. In addition, an interaction between smoking and alcohol consumption was suggested. However, causality should be interpreted carefully, as the present study did not assess sarcopenia status at baseline.
Notes
CONFLICT OF INTEREST
The researchers claim no conflicts of interest.
FUNDING
This work was supported by JSPS KAKENHI (Grant No. JP23249035 and JP23790708); the National Cancer Center Research and Development Fund [23-A31(toku) (since 2010)]. Data collection from the Uonuma cohort was supported by Niigata Prefecture.
AUTHOR CONTRIBUTIONS
Conceptualization, TK, KeikoK, KN; Data curation, TK, RT; Funding acquisition, ST, KN; Investigation, KeikoK, KaoriK, YW, TK, YI, AT, TS, RK, RO, RT, JT, KN; Methodology, KeikoK, KN; Project administration, YI, SY, KN; Supervision, ST, KW, SY; Formal analysis, TK, KN; Writing_original draft, TK, KeikoK, KN; Writing_review & editing, YW, ST, KW.
SUPPLEMENTARY MATERIALS
Supplementary materials can be found via https://doi.org/10.4235/agmr.26.0074.
Differences in percent frequencies of age, sex, smoking, and alcohol consumption at baseline between the present sample and the original total sample
Codes for demographic variables
Participant characteristics at the 2011–2014 baseline survey according to levels of smoking by sex
Participant characteristics at the 2011–2014 baseline survey according to levels of alcohol consumption by sex
Details of participant characteristics of marital status, education level, and alcohol consumption at the 2011–2014 baseline survey according to levels of smoking
Details of participant characteristics of marital status, education level, and smoking at the 2011–2014 baseline survey according to levels of alcohol consumption
Participant characteristics in the 2021–2022 physical examinations by sex
Sensitivity analyses of odds ratios (ORs) for presence of sarcopenia according to alcohol consumption categories–
