Abstract
Background
Empirical evidence concerning the association between household food insecurity and objectively quantified low muscle mass, together with the nutritional mechanisms underlying this link, remains limited. The present study aimed to examine the relation between food insecurity and the odds of low muscle mass in a nationally representative sample of U.S. adults and to determine whether total intakes of protein, vitamin D, and calcium mediate this relation.
Methods
A cross-sectional analysis was conducted using data from 6 292 adults (≥ 18 years) enrolled in the 2011–2018 National Health and Nutrition Examination Survey. Household food security was assessed with the 10-item USDA Adult Food Security Survey Module (12-month reference period). Habitual nutrient intakes were estimated from two non-consecutive 24-h dietary recalls obtained with the Automated Multiple-Pass Method and analysed with the Food and Nutrient Database for Dietary Studies, thereby capturing both food- and supplement-derived nutrients. Low muscle mass was defined by dual-energy X-ray absorptiometry as an appendicular lean-mass index < 7.0 kg m-2 in men or < 5.5 kg m-2 in women (EWGSOP criteria). Survey-weighted generalised linear models yielded adjusted odds ratios (ORs), and non-parametric bootstrap procedures (5 000 iterations) were applied to quantify mediation.
Results
Food insecurity was identified in 22.6 % of participants. After adjustment for socio-demographic and health-related covariates, food insecurity was associated with higher odds of low muscle mass (OR = 1.38; 95 % CI 1.01–1.88). Lower total protein intake accounted for 6.3 % of this association (average causal mediation effect =–0.00093; p = 0.048), whereas intakes of vitamin D and calcium did not exert significant indirect effects. Age, body-mass index, sex and ethnicity were additional independent correlates of low muscle mass.
Conclusions
Household food insecurity is independently associated with increased odds of low muscle mass in U.S. adults, and inadequate protein intake constitutes a significant—albeit partial—mediating pathway. Prospective and interventional investigations are warranted to establish temporal directionality and to evaluate whether improving dietary protein adequacy can modify this relationship.
Keywords: Nutrition surveys, Body composition, Cross-Sectional studies
Introduction
With the growing disparities in global economic and social development, food security has garnered increasing attention [1, 2]. Beyond ensuring an adequate food supply, food security encompasses dietary composition and nutritional status, which are critical determinants of overall health outcomes [3, 4]. In recent years, low muscle mass has been identified as an independent health risk factor, strongly linked to an increased risk of falls, functional deterioration, and the progression of chronic diseases in the elderly population [5, 6]. Limited research has been conducted on the relationship between food security and muscle mass, with existing literature primarily focusing on the impact of malnutrition on muscle function [7, 8].
Emerging evidence has demonstrated that protein, vitamin D, and calcium are fundamental to muscle synthesis and function. Adequate protein intake facilitates muscle anabolism [9, 10], while the regulatory mechanisms of vitamin D and calcium metabolism contribute to the maintenance of muscle integrity [11–13]. Some studies have suggested that the effects of these nutritional supplements may be overstated and, in practice, may not be as effective as initially anticipated [14, 15]. Inadequate intake of protein, vitamin D, and calcium has been identified as a significant and non-negligible indicator of food insecurity. Among women, children, and older adults, such nutritional deficiencies are often associated with more pronounced adverse health outcomes [16–18]. Investigating the impact of food security status on muscle mass through its influence on the intake of these essential nutrients is of substantial public health importance, particularly for the formulation of targeted intervention strategies.
Although numerous studies have explored food insecurity, to date, no investigation has concurrently quantified the association between household food insecurity and objectively assessed low muscle mass, nor examined the mediating effects of specific nutrient intakes within a nationally representative sample of the United States population. In the present study, a cross-sectional analysis was conducted using data from the 2011–2018 National Health and Nutrition Examination Survey (NHANES) to evaluate the association between food insecurity and the odds of low muscle mass in adults, accounting for potential confounding variables. Furthermore, the mediating roles of protein, vitamin D, and calcium intake in this association were systematically assessed.
Methods and patients
Study design and population
This cross-sectional study analysed data from the 2011–2018 National Health and Nutrition Examination Survey (NHANES), a complex, multistage probability sample of the non-institutionalised U.S. population. NHANES conducted by the National Center for Health Statistics (NCHS), is a comprehensive, ongoing national survey designed to evaluate the health and nutritional status of the U.S. population through structured interviews, physical examinations, and laboratory assessments. The study protocols were approved by the NCHS Research Ethics Review Board, and written informed consent was obtained from all participants. For the present analysis, this study utilized publicly available data from the NHANES 2011–2018.
Participants were included from the NHANES database based on the following criteria: Participants aged ≥ 18 y with valid dual-energy X-ray absorptiometry (DXA) scans and complete data on adult food-security status were eligible. Exclusion criteria were: (1) pregnancy or lactation; (2) body mass index (BMI) ≥ 50 (extreme obesity may bias DXA readings); (3) self-reported active malignancy; (4) missing covariate information.
Assessment of food security
Household food security was evaluated using the 10-item Adult Food Security Survey Module developed by the United States Department of Agriculture (USDA), which is a psychometrically validated instrument commonly employed in epidemiological research. This module comprises ten dichotomous (yes/no) items designed to capture food-related experiences and behaviors within the preceding 12 months. It has been extensively implemented in nationally representative surveys and has consistently demonstrated robust reliability and construct validity across diverse demographic groups. These items include assessments of concerns about food insufficiency, financial limitations affecting food availability, and the inability to afford a nutritionally balanced diet.
Food security status was classified into four categories according to the criteria established by the United States Department of Agriculture (USDA): full food security (0 affirmative responses), marginal food security (1–2 affirmative responses), low food security (3–5 affirmative responses), and very low food security (6–10 affirmative responses). In this study, full and marginal food security were combined into the “food security status” category, while low and very low food security were categorized as “food insecurity status” to systematically investigate the impact of food insecurity on muscle mass.
Assessment of muscle mass
This study evaluated muscle mass using Dual-energy X-ray Absorptiometry (DXA) data from the NHANES. DXA is a well-established and highly precise imaging modality widely utilized for the assessment of muscle mass, bone mineral density, and adipose tissue composition. In this study, appendicular lean mass (ALM) was derived from DXA measurements, calculated as the sum of lean soft tissue mass (kg) in the upper and lower limbs. To account for individual body size differences, the ALM index (ALMI) was employed, defined as ALM divided by the square of height (ALM/height², kg/m²). This index is widely recognized for muscle mass assessment and provides a standardized metric for evaluating muscle mass independent of overall body size.
The definition of low muscle mass in this study was based on the criteria established by the European Working Group on Sarcopenia in Older People (EWGSOP), which specifies ALMI < 7.0 kg/m² in males and ALMI < 5.5 kg/m² in females [6]. Based on these criteria, participants were classified into normal muscle mass and low muscle mass groups to facilitate further investigation into the relationship between food security status and muscle mass.
Dietary intake assessment
The objective of the dietary interview component is to obtain detailed dietary intake information from NHANES participants. The dietary intake data are used to estimate the types and amounts of foods and beverages (including all types of water) consumed during the 24-hour period prior to the interview (midnight to midnight), and to estimate intakes of energy, nutrients, and other food components from those foods and beverages. Following the dietary recall, participants are asked questions on salt use, whether the person’s overall intake on the previous day was much more than usual, usual or much less than usual, and whether the participant is on any type of special diet. Dietary intake data were obtained from two non-consecutive 24-h dietary recalls administered with the USDA Automated Multiple-Pass Method. The first recall was conducted in-person at the Mobile Examination Center (MEC); the second was collected by telephone 3–10 days later. Total nutrient intakes (protein, vitamin D, calcium) were calculated with the Food and Nutrient Database for Dietary Studies (FNDDS 2017–2018 for the latest cycle) and averaged across the two recalls to approximate usual intake. Both food and dietary-supplement sources were included.
Covariates
Covariates included both sociodemographic and health-related variables. Sociodemographic variables comprised sex, age, ethnicity, education level, and family income-to-poverty ratio. Sex was categorized as male and female; age was recorded as the participants’ actual age in years; ethnicity was classified into Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Asian, and Other ethnicities (including multi-racial); the education level was classified as follows: low education level was defined as having completed high school or lower; medium education level was defined as having completed high school; and high education level was defined as having completed a college degree or higher; family income-to-poverty ratio was used to classify participants into two groups: family income-to-poverty ratio (PIR) was dichotomised as < 1.00 (below Federal poverty threshold) or ≥ 1.00 (at/above threshold).
Health-related variables included BMI, hypertension, diabetes, smoking status, and alcohol consumption. BMI, calculated as weight (kg) divided by height (m²), was treated as a continuous variable; hypertension was defined as a prior diagnosis of hypertension by a physician or the use of antihypertensive medications, categorized as “Yes” or “No”; diabetes was defined as a prior diagnosis of diabetes by a physician or the use of antidiabetic medications, also categorized as “Yes” or “No”; smoking and alcohol consumption were each defined by current smoking and drinking status, categorized as “Yes” or “No.” Finally, low muscle mass was treated as a binary variable, classified according to the criteria for low muscle mass.
All these covariates were considered potential confounders and were controlled for in the statistical analyses to ensure the accuracy and reliability of the study’s findings.
Statistical analysis
Descriptive statistical analysis was initially performed to compare the baseline characteristics, including demographic and health-related variables, across different food security groups. To assess the relationship between food security and low muscle mass, univariate analysis was conducted using the Cochran-Armitage Trend Test. Subsequently, a GLM was employed for multivariate analysis to explore the association between food security and low muscle mass. The GLM is appropriate for various types of dependent variables (such as binary or continuous outcomes) and allows for adjustment of covariates while incorporating the sample weights provided by the NHANES database.
To further investigate whether dietary factors (such as protein, vitamin D, and calcium intake) mediate the relationship between food security and low muscle mass, a causal mediation analysis was performed. This analysis utilized nonparametric bootstrap resampling with 5000 iterations to estimate the average causal mediation effect (ACME), average direct effect (ADE), and total effect, and to compute 95% confidence intervals based on percentiles. The mediation effect was quantified as the ratio of ACME to total effect, reflecting the mediating role of dietary factors in the association between food security and low muscle mass.
Variance inflation factors (VIF) were calculated to evaluate multicollinearity among the covariates, ensuring that excessive correlations did not exist between them and thereby confirming the robustness and validity of the model. All statistical analyses were conducted using R software version 4.2.0, with statistical significance defined as a two-sided p-value of < 0.05.
Results
This study included data from the 2011–2018 NHANES dataset, comprising a total of 39,156 participants. After excluding cases with missing data, 6,292 participants were retained for analysis (Fig. 1). The baseline characteristics of the study population are presented in Table 1.
Fig. 1.
Selection of 6,292 participants from the NHANES 2011–2018 dataset (n = 39,156) after excluding individuals with missing data for key variables
Table 1.
Baseline characteristics of the study population
| Variable | Category | Low muscle mass | No low muscle mass | Total |
|---|---|---|---|---|
| Sample size | 558 | 5734 | 6292 | |
| Age (years) | Median (IQR) | 36.0 (25.2, 49.0) | 40.0 (30.0, 49.0) | 39.0 (29.0, 49.0) |
| BMI (kg/m²) | Median (IQR) | 20.6 (19.0, 22.4) | 28.6 (25.0, 33.3) | 27.8 (24.0, 32.6) |
| Sex | Male | 207 (37.1%) | 2894 (50.5%) | 3101 (49.3%) |
| Female | 351 (62.9%) | 2840 (49.5%) | 3191 (50.7%) | |
| Ethnicity | Mexican American | 50 (8.96%) | 812 (14.16%) | 862 (13.7%) |
| Other Hispanic | 54 (9.68%) | 561 (9.78%) | 615 (9.77%) | |
| Non-Hispanic White | 231 (41.4%) | 2197 (38.32%) | 2428 (38.59%) | |
| Non-Hispanic Black | 37 (6.63%) | 1321 (23.04%) | 1358 (21.58%) | |
| Non-Hispanic Asian | 170 (30.47%) | 614 (10.71%) | 784 (12.46%) | |
| Other | 16 (2.87%) | 229 (3.99%) | 245 (3.89%) | |
| Education level | Low | 75 (13.44%) | 933 (16.27%) | 1008 (16.02%) |
| Medium | 102 (18.28%) | 1249 (21.78%) | 1351 (21.47%) | |
| High | 381 (68.28%) | 3552 (61.95%) | 3933 (62.51%) | |
| Income-to-poverty ratio | < 1 | 142 (25.45%) | 1255 (21.89%) | 1397 (22.2%) |
| ≥ 1 | 416 (74.55%) | 4479 (78.11%) | 4895 (77.8%) | |
| Smoking status | Yes | 212 (37.99%) | 2270 (39.61%) | 2482 (39.47%) |
| No | 346 (62.01%) | 3461 (60.39%) | 3807 (60.53%) | |
| Alcohol consumption | Yes | 388 (69.53%) | 4368 (76.16%) | 4756 (75.58%) |
| No | 170 (30.47%) | 1366 (23.84%) | 1536 (24.42%) | |
| Hypertension | Yes | 70 (12.7%) | 1417 (24.7%) | 1487 (23.6%) |
| No | 488 (87.3%) | 4317 (75.3%) | 4805 (76.3%) | |
| Diabetes | Yes | 29 (4.5%) | 439 (7.7%) | 468 (7.4%) |
| No | 529 (94.3%) | 5176 (90.3%) | 5705 (90.7%) | |
| Food security | Yes | 449 (80.47%) | 4424 (77.15%) | 4873 (77.45%) |
| No | 109 (19.53%) | 1310 (22.85%) | 1419 (22.55%) | |
| Daily protein intake (gm) | Median (IQR) | 71.5 (54.7, 93.3) | 80.0 (60.3, 104.1) | 79.2 (59.8, 103.2) |
| Daily vitamin d intake (mcg) | Median (IQR) | 3.1 (1.6, 5.4) | 3.4 (1.7, 5.9) | 3.4 (1.7, 5.9) |
| Daily calcium intake (mg) | Median (IQR) | 799.8 (543.1, 1098.4) | 872.2 (613.0, 1199.0) | 864.5 (605.5, 1190.0) |
IQR, interquartile range
The proportion of low muscle mass was lower in the food secure group compared to the food insecure group (Fig. 2). The secure group exhibited higher protein and calcium intake, with greater variability, compared to the insecure group. Vitamin D intake was similar across both groups. These findings highlight the association between food security and higher nutrient intake, particularly for protein and calcium (Fig. 3). These plots are descriptive, inferential statistics are reported in the following paragraphs.
Fig. 2.
Stacked bar chart illustrating the percentage distribution of muscle mass status (Non-Low Muscle Mass: blue; Low Muscle Mass: yellow) across food security categories (Secure vs. Insecure)
Fig. 3.
Violin plots showing the distribution of daily protein, vitamin D, and calcium intake by food security status (Secure vs. Insecure). The secure group (purple/orange) generally exhibits higher protein and calcium intake, while vitamin D intake shows minimal variation. Boxplots indicate the median and interquartile range, with violin widths representing data density
A Cochran-Armitage trend test was performed to examine the association between food security and low muscle mass. The result demonstrated a chi-square statistic of 0.39242 and a p-value of 0.531, indicating no statistically significant association between food security status and the prevalence of low muscle mass (p > 0.05). These findings suggest that food security did not demonstrate a significant trend in relation to low muscle mass.
A GLM was conducted to assess the association between food security and low muscle mass, adjusting for potential covariates, including age, BMI, sex, ethnicity, education level, income-to-poverty ratio, smoking status, alcohol consumption, hypertension, and diabetes (Fig. 4). Food insecurity was significantly associated with a lower likelihood of low muscle mass (odds ratio [OR] = 0.726, 95% CI: 0.531–0.995, p = 0.046). Additionally, significant associations were observed for age (OR = 1.038, 95% CI: 1.026–1.050, p < 0.001) and BMI (OR = 0.478, 95% CI: 0.449–0.506, p < 0.001), indicating that older age and lower BMI were associated with higher odds of low muscle mass. Sex also played a role, with females exhibiting higher odds of low muscle mass compared to males (OR = 1.405, 95% CI: 1.094–1.806, p = 0.008). Ethnicity showed significant differences, with non-Hispanic Black individuals having much lower odds of low muscle mass (OR = 0.097, 95% CI: 0.054–0.171, p < 0.001), while individuals in the “Other” ethnic category had higher odds (OR = 0.321, 95% CI: 0.144–0.684, p = 0.004). No significant associations were found for education level, income-to-poverty ratio, smoking status, alcohol consumption, hypertension, or diabetes (p > 0.05 for all).
Fig. 4.
Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) are shown on a logarithmic scale. The dashed black line at OR = 1 indicates no association. Age and diabetes increased risk, while higher BMI was protective. Significant variables: purple (P < 0.001), blue (P < 0.05), gray (P ≥ 0.05)
The analysis utilized bootstrap resampling with 5000 iterations to estimate the ACME, ADE, and total effect for each mediator (Table 2). The results indicated that protein intake significantly mediated the relationship between food security and low muscle mass. The ACME for protein intake was − 0.00093 (95% CI: −0.00198 to −0.00019, p = 0.048), the ADE was − 0.01380 (95% CI: −0.02997 to −0.0001, p = 0.038), and the total effect was − 0.01473 (95% CI: −0.03095 to −0.00395, p = 0.032), with approximately 6.3% of the total effect mediated by protein intake (proportion mediated = 0.06300, 95% CI: −0.01300 to 0.330, p = 0.082). In contrast, vitamin D intake did not show a significant mediation effect, as the ACME was 0.00046 (95% CI: −0.00034 to 0.00046, p = 0.262), and the proportion mediated was not significant (proportion mediated = −0.02700, 95% CI: −0.14000 to 0.278, p = 0.278). For calcium intake, no significant mediation effect was observed (ACME = 0.00021, 95% CI: −0.00070 to 0.00060, p = 0.626), though the ADE for calcium intake was significant (ADE = −0.01634, 95% CI: −0.03250 to −0.0021, p = 0.022) with a total effect of −0.01612 (95% CI: −0.03261 to −0.0018, p = 0.022), and the proportion mediated was not significant (proportion mediated = −0.01300, 95% CI: −0.14600 to 0.628, p = 0.628).
Table 2.
Causal Mediation Analysis Results Based on Bootstrap Estimation
| Mediator | Estimate | Point estimate | 95% CI lower | 95% CI upper | p-value |
|---|---|---|---|---|---|
| Protein intake | ACME (average) | −0.00093 | −0.00198 | 0.000 | 0.048 |
| ADE (average) | −0.01380 | −0.02997 | 0.000 | 0.038 | |
| Total Effect | −0.01473 | −0.03095 | 0.000 | 0.032 | |
| Proportion Mediated (average) | 0.06300 | −0.01300 | 0.330 | 0.082 | |
| Vitamin D intake | ACME (average) | 0.00046 | −0.00034 | 0.000 | 0.262 |
| ADE (average) | −0.01756 | −0.03390 | 0.000 | 0.014 | |
| Total Effect | −0.01709 | −0.03313 | 0.000 | 0.016 | |
| Proportion Mediated (average) | −0.02700 | −0.14000 | 0.278 | 0.278 | |
| Calcium intake | ACME (average) | 0.00021 | −0.00070 | 0.000 | 0.626 |
| ADE (average) | −0.01634 | −0.03250 | 0.000 | 0.022 | |
| Total Effect | −0.01612 | −0.03261 | 0.000 | 0.022 | |
| Proportion Mediated (average) | −0.01300 | −0.14600 | 0.628 | 0.628 |
ACME (Average Causal Mediation Effect) represents the indirect effect through the mediator, while ADE (Average Direct Effect) captures the direct effect. Total Effect is the sum of ACME and ADE, and Proportion Mediated is ACME divided by Total Effect, indicating the proportion of mediation.
VIF were computed to assess potential multicollinearity among the covariates included in the generalized linear model. The VIF values for the covariates ranged from 1.099944 (for sex) to 1.496699 (for ethnicity), and the adjusted VIF (Adj_VIF) values ranged from 1.048782 (for sex) to 1.199884 (for income-to-poverty ratio). All VIF values were well below the threshold of 10, indicating that multicollinearity was not a concern in the model. These findings confirm the robustness and validity of the model, ensuring that the predictor estimates were not unduly influenced by multicollinearity.
Discussion
This study based on an analysis of the 2011–2018 NHANES dataset, identified the relationship between food security and low muscle mass in adults and further examined the mediating effects of average daily intake of protein, vitamin D, and calcium. The findings revealed that food insecurity was significantly associated with an increased odds of low muscle mass, with protein intake acting as a mediator in this association.
In our weighted NHANES sample, 22.55% of adults were food-insecure—still nearly double the 2022 U.S. national household estimate of 12.8%. Similar or even higher prevalences are reported in younger populations: a scoping review of 51 U.S [19]. college-student samples found food-insecurity rates spanning 10–75% (pooled ≈ 33%), and Mexican data from 7 659 university-student households showed that more than half experienced some degree of food insecurity, which was linked to lower adherence to healthy dietary patterns [16]. Food insecurity was typically associated with limited food availability and an unbalanced diet, leading to inadequate nutrient intake, which in turn affected muscle mass [20, 21]. This was particularly relevant for economically disadvantaged populations, where deficiencies in key nutrients such as protein, vitamin D, and calcium increased the odds of muscle loss [22]. In this study, the Cochran-Armitage Trend Test did not demonstrate a statistically significant association between food security and low muscle mass. However, in the multivariable analysis, a significant association was observed between food insecurity and the occurrence of low muscle mass (OR = 0.726, 95% CI: 0.531–0.995, p = 0.046). These results were consistent with previous findings, which emphasized the substantial impact of socioeconomic factors, such as food security, on health and nutritional status [23].
Shan et al. conducted a consecutive cross-sectional analysis of the NHANES database from 1999 to 2016 and observed a decline in the proportion of total carbohydrate intake among U.S. adults, whereas the proportions of protein and fat intake increased. Although improvements were noted in the dietary macronutrient composition and overall dietary quality, the consumption of low-quality carbohydrates and saturated fats remained elevated [24]. These findings indicate that the intake ratios of essential nutrients in adults still require optimization. Additionally, the excessive use of dietary supplements has been demonstrated to have no significant effects [25]. A more appropriate approach would be the development of individualized nutrition plans [26].
Ouyang et al. conducted a cross-sectional study to investigate the association between dietary protein intake, its distribution, and muscle mass among Chinese adults aged 60 years and above. The findings indicated that, in comparison with the lowest protein intake group, individuals in the highest intake group exhibited greater muscle mass, with an increase of 0.96 kg in males and 0.48 kg in females [27]. The authors concluded that enhancing total daily protein intake may be beneficial for maintaining muscle mass in the older adult population. In the present study, daily protein, vitamin D, and calcium intake were also included as mediating variables. Protein intake was found to play a significant mediating role between food security and low muscle mass (ACME = −0.00093, 95% CI: −0.00198 to −0.00019, p = 0.048). Although vitamin D and calcium intake are important components of nutritional intake, they did not show a significant mediating effect in this study.
Protein was identified as a critical nutrient for muscle synthesis and repair, and a reduction in its intake was found to significantly decrease muscle mass, particularly in malnourished populations [28]. Nutritional interventions were recommended to focus on increasing protein intake in food-insecure groups to prevent and delay muscle degeneration. A systematic review and meta-analysis encompassing 74 randomized controlled trials demonstrated that increased dietary protein intake was associated with a modest yet statistically significant augmentation in lean body mass (standardized mean difference [SMD] = 0.22), particularly among individuals aged 65 years and older [29]. However, protein supplementation exceeding 1.6 g/kg/day did not yield further significant benefits [30]. While protein plays a crucial role in muscle synthesis and repair, it should be supplemented in appropriate amounts. Animal-derived protein appeared to be more beneficial than plant-based protein for individuals with lower lean body mass [31]. Additionally, higher protein intake at breakfast was shown to provide greater benefits than intake at other times of the day [32].
Previous studies have indicated that calcium and vitamin D intake might serve as important nutritional factors influencing muscle health [33, 34]. However, no significant mediating effect was observed in this study. The intake of vitamin D and calcium may also require appropriate amounts, as high doses or excessive intake may not result in significant benefits. A review indicated that both dietary intake and serum concentrations of vitamin D are consistently suboptimal in many countries worldwide, primarily due to seasonal fluctuations in ultraviolet B (UVB) radiation and the limited availability of foods naturally rich in vitamin D. The absorption efficiency of vitamin D2 varies substantially across different food matrices, whereas vitamin D3 demonstrates favorable bioavailability in various dietary sources. Alterations in the lipid composition of food have been shown to enhance the intestinal absorption of vitamin D3 [35]. The development of nutrition plans tailored to different populations may be more appropriate to address current needs.
This study elucidated the association between food insecurity and low muscle mass in adults, underscoring the potential health risks associated with food insecurity. Enhancing nutritional interventions for low-income and vulnerable populations, particularly those aimed at increasing protein intake, may contribute to the prevention and alleviation of low muscle mass, thereby improving the overall health of these populations. For individuals experiencing food insecurity, particularly the elderly, the development of personalized nutritional interventions is essential.
Future research could further investigate the relationship between food security and muscle mass from various perspectives. Longitudinal studies would be beneficial in establishing the causal relationship between food insecurity and low muscle mass, as well as in assessing the long-term effects of food insecurity on muscle health. Further studies should also examine other potential nutritional factors, such as micronutrients and dietary fats, and their impact on muscle mass. Future research could explore the efficacy of multi-faceted intervention strategies, incorporating nutritional supplementation, physical activity, and social support, to improve muscle mass and overall health in food-insecure populations.
This study has several limitations. Firstly, as it utilized cross-sectional data, it was unable to establish a causal relationship between food insecurity and low muscle mass. Secondly, the study relied on self-reported data, such as food security status and certain health variables, which may be subject to reporting bias. Thirdly, although the study controlled for several potential confounding factors, the influence of other unmeasured variables could not be ruled out. Lastly, despite using the NHANES data, the sample only represents the U.S. adult population and may not be fully generalizable to populations in other countries or regions. The lack of objectively measured physical activity data represents a methodological limitation of the present study and may have introduced measurement bias into the observed associations. Moreover, the application of ALMI thresholds to define low muscle mass among participants aged 18–59 years may lead to an underestimation of low muscle mass, given that the study population is relatively young in relation to the reference standards. Future research should include broader, multinational studies and multicenter clinical trials to validate these findings.
Conclusion
Household food insecurity is independently associated with higher odds of low muscle mass in U.S. adults, and that lower total protein intake significantly mediates this association. Interventions focused on improving protein intake in food-insecure populations, particularly those at risk of low muscle mass, could be an effective strategy for preventing and mitigating muscle degeneration.
Acknowledgements
The authors would like to acknowledge the use of data from the National Health and Nutrition Examination Survey (NHANES) 2011–2018, which was made publicly available by the National Center for Health Statistics. We also thank the participants of NHANES for their contribution to this study.
Code availablity
Not applicable.
Clinical trial number
Not applicable.
Abbreviations
- MEC
Mobile Examination Center
- USDA
United States Department of Agriculture
- ACME
Average Causal Mediation Effect
- ADE
Average Direct Effect
- ALMI
Appendicular Lean Mass Index
- BMD
Bone Mineral Density
- BMI
Body Mass Index
- CI
Confidence Interval
- DXA
Dual-energy X-ray Absorptiometry
- EWGSOP
European Working Group on Sarcopenia in Older People
- GLM
Multivariate Generalized Linear Models
- NCHS
National Center for Health Statistics
- NHANES
National Health and Nutrition Examination Survey
- OR
Odds Ratio
- USDA
United States Department of Agriculture
- VIF
Variance Inflation Factors
Authors’ contributions
Rong-Zhen Xie: Conceptualization, Writing – Original Draft, Data Curation, Software Analysis. Xu-Song Li: Data Curation, Software Analysis. Wei-Qiang Zhao: Literature Search. Yu-Feng Liang: Literature Search Assistance. Jie-Feng Huang: Supervision, Study Design, Manuscript Preparation, Critical Revisions.
Funding
There is no funding.
Data availability
The data used in this study were obtained from the National Health and Nutrition Examination Survey (NHANES) database. NHANES is a publicly available dataset provided by the Centers for Disease Control and Prevention (CDC) in the United States. The data can be accessed at the NHANES website (https://www.cdc.gov/nchs/nhanes/?CDC_AAref_Val=https://www.cdc.gov/nchs/nhanes/index.htm).
Declarations
Ethics approval and consent to participate
NHANES conducted by the National Center for Health Statistics (NCHS), is a comprehensive, ongoing national survey designed to evaluate the health and nutritional status of the U.S. population through structured interviews, physical examinations, and laboratory assessments. The study protocols were approved by the NCHS Research Ethics Review Board, and written informed consent was obtained from all participants. For the present analysis, we utilized publicly available data from the NHANES 2011–2018.
Consent for publication
All authors are consent to publish.
Competing interests
The authors declare no competing interests.
Acknowledgements.
Footnotes
This study was a cross-sectional analysis using data collected from the NHANES between 2011 and 2018. The NHANES protocol was approved by the Ethics Review Board of the National Center for Health Statistics, Centers for Disease Control and Prevention (CDC), and all participants provided written informed consent.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rong-Zhen Xie MS and Xu-Song Li PhD contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data used in this study were obtained from the National Health and Nutrition Examination Survey (NHANES) database. NHANES is a publicly available dataset provided by the Centers for Disease Control and Prevention (CDC) in the United States. The data can be accessed at the NHANES website (https://www.cdc.gov/nchs/nhanes/?CDC_AAref_Val=https://www.cdc.gov/nchs/nhanes/index.htm).