Skip to main content Accessibility help
×
Home

Association of protein intake with the change of lean mass among elderly women: The Osteoporosis Risk Factor and Prevention – Fracture Prevention Study (OSTPRE-FPS)

Published online by Cambridge University Press:  16 December 2015

Masoud Isanejad
Affiliation:
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, PO Box 1627 Kuopio, Finland
Jaakko Mursu
Affiliation:
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, PO Box 1627 Kuopio, Finland
Joonas Sirola
Affiliation:
Department of Orthopaedics and Traumatology, Kuopio University Hospital, Kuopio, Finland Kuopio Musculoskeletal Research Unit (KMRU), University of Eastern Finland, Kuopio, Finland
Heikki Kröger
Affiliation:
Department of Orthopaedics and Traumatology, Kuopio University Hospital, Kuopio, Finland Kuopio Musculoskeletal Research Unit (KMRU), University of Eastern Finland, Kuopio, Finland
Toni Rikkonen
Affiliation:
Kuopio Musculoskeletal Research Unit (KMRU), University of Eastern Finland, Kuopio, Finland
Marjo Tuppurainen
Affiliation:
Department of Obstetrics and Gynaecology, Kuopio University Hospital, Kuopio, Finland
Arja T. Erkkilä
Affiliation:
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, PO Box 1627 Kuopio, Finland
Corresponding
E-mail address:

Abstract

Low protein intake can lead to declined lean mass (LM) in elderly. We examined the associations of total protein (TP), animal protein (AP) and plant protein (PP) intakes with LM. The association of TP intake with LM change was further evaluated according to weight change status. This cross-sectional and prospective cohort study included 554 women aged 68 (sd 1·9) years from the Osteoporosis Risk Factor and Prevention – Fracture Prevention Study (OSTPRE-FPS). The intervention group (n 270) received daily cholecalciferol (800 IU; 20 μg) and Ca (1000 mg) for 3 years while the control group received neither supplementation nor placebo (n 282). Participants filled out a questionnaire on lifestyle factors and a 3-d food record in 2002 and underwent dual-energy X-ray absorptiometry for body composition measurements at baseline and 3 years. Multiple linear regressions evaluated the association between protein intake and LM, adjusting for relevant covariates. At the baseline TP and AP intakes were positively associated with LM and trunk LM, TP was associated also with appendicular LM (aLM). Follow-up results showed that in the total population and the intervention group, higher TP and AP were associated with increased LM and aLM (P ≤ 0·050). No such associations were observed in the control group. PP intake was also associated with aLM change in the total population. Overall, the associations were independent of fat mass. Further, among weight maintainers, TP intake was positively associated with LM, aLM and trunk LM changes (P ≤ 0·020). In conclusion, dietary TP, especially AP, intake may be a modifiable risk factor for sarcopenia by preserving LM in the elderly.

Type
Research Article
Creative Commons
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s) 2015

The sarcopenic phenotype is characterised by an absolute or relative reduction in lean mass (LM) which can lead to increased risk of fractures, frailty and loss of independence( Reference Muller, Geisler and Pourhassan 1 , Reference Cruz-Jentoft, Baeyens and Bauer 2 ). Older adults over the age of 50 years lose approximately 1–2 % of LM per year( Reference Hughes, Frontera and Roubenoff 3 ). However, the aetiology of LM loss is multifactorial. Dietary protein intake has been considered as one potential contributor to LM change which can determine the balance between protein synthesis and the protein breakdown rate in muscles( Reference Cruz-Jentoft, Baeyens and Bauer 2 , Reference Evans 4 ). Current evidence suggests that age-related loss of LM may be halted or even reversed by increased daily protein intake( Reference Houston, Nicklas and Ding 5 Reference Meng, Zhu and Devine 7 ). The quality of protein intake additionally may play a role in determining the LM. Putatively, animal protein (AP) provides more essential amino acids in comparison with plant protein (PP) sources which can stimulate muscle protein synthesis (MPS)( Reference Lord, Chaput and Aubertin-Leheudre 8 Reference Paddon-Jones and Rasmussen 10 ). Vitamin D supplementation further might affect LM directly through different mechanisms. It has been suggested also that vitamin D supplementation might have a synergic relationship with dietary protein intake in increasing LM( Reference Beaudart, Buckinx and Rabenda 11 Reference Salles, Chanet and Giraudet 15 ). However, little is known regarding the interaction between vitamin D supplementation and dietary protein intake and LM and further studies are warranted.

Although data to support guideline for weight-loss treatment in elderly are limited, one of the main targets was the preservation of LM by adequate protein intake( Reference Mathus-Vliegen 16 ). It is well known that dietary protein intake may affect LM and fat mass (FM) partitioning during weight loss( Reference Pedersen and Cederholm 17 ). Thus, evaluating the protein intake association with body composition during weight changes may have important implications among elderly who tend to lose weight.

The primary objective of the present study was to examine the associations of total protein (TP), AP and PP intakes with LM at baseline and changes over a 3-year follow-up among elderly women. A secondary objective was to evaluate the association of TP with change of LM according to weight-change status.

Subjects and methods

Study population

Data of the present study were collected from the Osteoporosis Risk Factor and Prevention – Fracture Prevention Study (OSTPRE-FPS), which was a 3-year intervention to investigate the effect of Ca and vitamin D supplementation on incidence of falls and fractures among elderly women. The subjects were drawn from the population-based OSTPRE cohort( Reference Karkkainen, Tuppurainen and Salovaara 18 ). In total 3432 women volunteered to participate in the study, and 750 women were further randomly invited into this subsample for participating in detailed examinations including the measurement of body composition, and several clinical, physical and laboratory tests( Reference Jarvinen, Tuppurainen and Erkkila 19 ). Of these, 554 returned valid food records and had valid body composition measurements for both the baseline and at the 3-year follow-up. The intervention group (n 270) received daily cholecalciferol (800 IU; 20 μg) and Ca (1000 mg) for 3 years while the control group received neither supplementation nor placebo (n 282)( Reference Karkkainen, Tuppurainen and Salovaara 18 ). All participants provided written permission for participation. The study was approved in October 2001 by the ethical committee of Kuopio University Hospital. The study was registered in Clinical trials.gov by the identification NCT00592917( Reference Karkkainen, Tuppurainen and Salovaara 18 ).

Body composition measurements

Height and weight of participants were measured in light indoor clothing without shoes, and BMI was calculated (kg/m2). To measure body composition, whole-body dual-energy X-ray absorptiometry scans were performed by specially trained nurses, using the same Lunar Prodigy adhering to the imaging and analysis protocols provided by the manufacturer (Lunar Co.)( Reference Lohman, Tallroth and Kettunen 20 , Reference Kroger, Heikkinen and Laitinen 21 ). Appendicular LM (aLM) was calculated as the sum of the non-fat, non-bone skeletal muscle mass in arms and legs. Further, absolute changes in LM, aLM and trunk LM were calculated by subtracting the baseline values from those measured at year 3.

Dietary intakes

Dietary intake was collected by using 3-d food records at baseline. A questionnaire and instructions were sent to participants beforehand, and they were returned on the visiting day. The questionnaire was for three consecutive days, including 2 d during the week and 1 d in the weekend (Saturday or Sunday). In the case of uncertainties in the food record, a nutritionist called the participant for additional information( Reference Erkkila, Jarvinen and Karvonen 22 ). To assess the under-reporting the energy intake:estimated BMR ratio was calculated based on body weight (BW) according to equations given by the Department of Health in the UK( 23 ). The energy intake:BMR cut-off value for under-reporting was chosen to be 1·49, as derived from Goldberg et al.( Reference Goldberg, Black and Jebb 24 ) and Black( Reference Black 25 ) and none of the participants was excluded from the analyses. Nutritional intake from food was calculated using the Nutrica program (version 2.5; Finnish social insurance institute, Turku, Finland). Collected data provided calculations of AP (including eggs, dairy products, poultry and meat) and PP sources (cereals, vegetables and fruits) of protein in addition to TP intake.

Potential confounders

All lifestyle-related information was gathered by the self-administered questionnaire. The questionnaire included questions on age, smoking status (never, former and current), alcohol consumption (portions per week), use of hormone therapy (never used and used) and self-reported vitamin D supplementation. Physical activity level was compiled from frequency of exercise (times per week) and mobility status (restricted or non-restricted). Women were classified as passive if they had restricted or no mobility and exercised ≤2 times/week and those with no mobility restriction and who exercised >2 times/week were classified as active.

Statistical analysis

All statistical analyses were executed using SPSS software version 21 for Windows (IBM Corp.). A result was significant if the P value was <0·05. The protein intakes (TP, AP and PP) were adjusted for energy intake utilising the residual method( Reference Willett, Howe and Kushi 26 ). An advantage of this method is that it provides a measure of protein intake which is independent of total energy intake. Energy-adjusted protein intake (g/d) was modelled as a continuous variable and categorised into quartiles. Protein intake (g/kg BW) was calculated using crude protein intake divided by BW.

Continuous variables were compared across the quartiles of energy-adjusted TP intake using ANOVA and categorical variables using χ 2 tests. Multiple linear regression models were performed to examine the association between protein intake (g/d) as the independent variable with body composition measures as dependent variables, including LM, aLM and trunk LM at the baseline and changes in them over 3 years of follow-up. Follow-up associations of protein intake with changes in LM, aLM and trunk LM over 3 years of follow-up were explored separately between the intervention and control groups. Tests for a linear trend across quartiles of protein intake were conducted by using the median value in each quartile as a continuous variable in the linear regression model.

Model 1 was adjusted for age, height, total energy intake, study group and in longitudinal setting for baseline LM variables. Model 2 was adjusted for variables in model 1 plus smoking, alcohol use, physical activity level and hormone therapy use. Model 3 was adjusted for variables in model 2 plus baseline FM for cross-sectional setting and change of FM in prospective setting in order to determine whether the associations were independent of FM. For the models for AP and PP, the AP and PP intakes were included in the same regression model to adjust for each other.

We also examined the association between energy-adjusted protein intake (g/d) with LM measurements according to weight-change status. Those who lost over 3 % of their weight during the 3 years of follow-up were classified as weight losers, those who gained over 3 % were classified as weight gainers, and those with moderate change as weight maintainers. This 3 % cut-off was selected and applied to exceed the CV for dual-energy X-ray absorptiometry soft tissue mass( Reference Houston, Nicklas and Ding 5 , Reference Visser, Harris and Langlois 27 ).

Results

The participants were 65·3–71·6 years old; mean age was 68·0 (sd 1·9) years (Table 1). The energy intake was 6560 (sd 1556) kJ/d (1567 (sd 371) kcal), and mean total energy-adjusted protein intake was 68·2 g/d. Median TP intake as a percentage of total energy intake and protein (g/kg BW) by quartiles from quartile 1 to quartile 4 were 14·2 % (0·77 g/kg BW), 16·5 % (0·89 g/kg BW), 18·5 % (0·91 g/kg BW) and 20·1 % (1·17 g/kg BW). Women in the first and third quartiles of energy-adjusted protein intake were more likely to use hormone therapy (46 %) as compared with women in the second and fourth quartiles. Total fat intake (g/d) was highest in quartile 4 and energy intake was significantly higher in higher quartiles of protein intake. TP and AP intakes were significantly higher in higher quartiles of protein intake, while no significant association was observed for PP intake.

Table 1. Baseline characteristics of participants across quartiles of energy-adjusted total protein intake (g/d)

(Mean values and standard deviations; percentages)

FM, fat mass; LM, lean mass; aLM, appendicular LM.

* ANOVA or χ 2 tests were used to evaluate the distribution.

Passive: no mobility and exercise ≤2 times/week; active: no mobility restriction and exercise >2 times/week.

Those in the second and fourth quartiles had higher BW as compared with those in the first and third quartiles. LM, aLM and trunk LM were significantly increased with higher protein intake (Table 1). The absolute LM, aLM and trunk LM changes over the 3 years were +0·69, −0·27 and +0·48 %, respectively. Over the 3 years of follow-up, about 24 % of participants lost >3 % of their BW, 27 % of participants gained >3 % of their BW and 49 % were weight-maintainers (within ±3 % of baseline weight). Mean changes in aLM were a decrease of 0·57 (sd 0·95) kg in weight losers and 0·27 (sd 0·85) kg in weight maintainers and an increase of 0·19 (sd 1·2) kg among weight gainers. There were no significant differences in baseline characteristics between intervention and control groups (see Supplementary Table S1).

At baseline in model 3 energy-adjusted TP was positively associated with LM, aLM and trunk LM (β ≥ 0·05; P ≤ 0·014). AP intake (g/d) was positively associated with LM and trunk LM (β ≥ 0·08; P ≤ 0·010) (Table 2). AP intake was associated also with aLM in models 1 and 2; however, the association was no longer significant in model 3 after controlling for FM. No significant association was observed for PP intake except a non-significant association with trunk LM (β = 0·06; P = 0·083). Results were independent of FM. In the quartile analysis of protein intakes at baseline, women in higher quartiles of TP and AP, but not PP, had significantly greater LM, aLM and trunk LM (P trend ≤ 0·026) (data not shown).

Table 2. Cross-sectional association of protein intake and total lean mass (LM), appendicular LM (aLM) and trunk LM (n 554)

(β Coefficients with their standard errors)

* Model 1 was adjusted for age, total energy intake and baseline height and study group.

Model 2 was adjusted for variables in model 1 plus smoking status, alcohol use per week, physical activity level and hormone therapy use.

Model 3 was adjusted for variables in model 2 plus baseline fat mass.

§ Models for animal protein were also adjusted for plant protein intake.

|| Models for plant protein were also adjusted for animal protein intake.

Results for the prospective analysis are presented separately between intervention and control groups as well as the total population in Table 3. The interaction between energy-adjusted TP, AP and PP intake (g/d) and vitamin D and Ca supplementation was not significant (P ≥ 0·730). In model 3, in the intervention group energy-adjusted TP and AP but not PP intakes (g/d) were significantly associated with changes in LM and aLM (β ≥ 0·22; P = 0·001) over 3 years of follow-up. No significant association was observed in the control group except that PP was non-significantly associated with aLM change (β = 0·11; P = 0·082). In the total population in model 3, TP and AP were positively associated with LM and aLM changes over 3 years of follow-up (β ≥ 0·09; P ≤ 0·041). TP and AP were non-significantly associated also with trunk LM change (β = 0·08; P ≤ 0·088). PP intake in the total population was positively associated with aLM change (β = 0·09; P = 0·035) and non-significantly associated with LM change (β = 0·09; P ≤ 0·056) over 3 years of follow-up.

Table 3. Prospective association of protein intake and changes in total lean mass (LM), appendicular LM (aLM) and trunk LM between intervention and control groups and the total population

(β Coefficients with their standard errors)

* Model 1 was adjusted for age, total energy intake and baseline height and study group.

Model 2 was adjusted for variables in model 1 plus smoking status, alcohol use per week, physical activity level and hormone therapy use.

Model 3 was adjusted for variables in model 2 plus baseline fat mass.

§ Models for animal protein were also adjusted for plant protein intake.

|| Models for plant protein were also adjusted for animal protein intake.

In a follow-up analysis using quartiles of protein intakes in the intervention group, women in the highest quartiles of TP and AP intakes had significantly increased LM and aLM (P trend  0·001) as compared with those in the lower quartiles, while no such association was observed for PP intake. No significant association was observed in the control group. Further, in the total population, a non-significant association was observed between higher quartiles of TP and aLM change (P trend = 0·079) and PP intake was significantly associated with less decline in aLM (P trend = 0·027) (data not shown).

The association of energy-adjusted TP (g/d) with LM changes was further evaluated according to weight-change status. Weight change and energy-adjusted TP interactions were significant (P interaction < 0·001). Among weight maintainers, energy-adjusted TP (g/d) was associated with change in LM and aLM and trunk LM (β ≥ 0·13; P ≤ 0·020) (Table 4).

Table 4. Association of total protein intake (g/d) and changes of lean mass (LM), appendicular LM and trunk LM by weight change status (n 551)

(β Coefficients with their standard errors)

* Adjusted for age, total energy intake, baseline LM, aLM and trunk LM, height, smoking status, alcohol portions per week, physical activity level, hormone therapy use and study group.

Those who lost over 3 % of their baseline weight during the 3 years of follow-up were classified as weight losers, those who gained over 3 % as weight gainers, and those with moderate change as weight maintainers.

Discussion

The primary findings of this study were that at baseline higher energy-adjusted TP and AP intakes were positively associated with LM and trunk LM, and that TP intake was also associated with greater aLM. Follow-up results showed that in the intervention group as well as the total population higher TP and AP intakes were positively associated with changes in LM and aLM over 3 years of follow-up, while no significant association was observed in the control group. No such association was observed for PP intake except that in the total population PP intake was significantly associated with less decline in aLM over 3 years of follow-up. These associations remained significant even after adjusting for FM. Further, among weight maintainers TP intake was positively associated with LM, aLM and trunk LM changes.

Houston et al. showed that among women aged 70–79 years (n 2066), those with higher protein intake (19 % of total energy intake) lost 40 % less LM as compared with those with lower intake (11 % of total energy intake) over a 3-year follow-up( Reference Houston, Nicklas and Ding 5 ). Similarly, Meng et al. found that elderly women with higher TP intake (average >1·6 g/kg BW or 20·0 % of energy) had higher LM as compared with those with lower protein intake (average 0·85 g/kg BW or 18·0 % of energy)( Reference Meng, Zhu and Devine 7 ). The results from the present study were consistent with those previous studies suggesting that higher protein intake is beneficial to LM( Reference Houston, Nicklas and Ding 5 Reference Lord, Chaput and Aubertin-Leheudre 8 , Reference Geirsdottir, Arnarson and Ramel 28 ).

For older people (>65 years) to maintain and regain muscle mass and function, an average daily intake at least in the range of 1·0 to 1·2 g/kg BW is recommended( Reference Bauer, Biolo and Cederholm 29 , 30 ), which is higher than the current RDA (0·8 g/kg BW)( Reference Suominen, Jyvakorpi and Pitkala 31 ). A preponderance of evidence now suggests that ageing might result in the stimulation of MPS becoming resistant to the anabolic effect of hyperaminoacidaemia, particularly at lower protein intakes( Reference Paddon-Jones and Rasmussen 10 ). The decreased MPS might partially be explained by decreased mammalian target of rapamycin and the 70-kDa ribosomal protein S6 kinase signalling( Reference Eley, Russell and Baxter 32 ), and changes in positive regulators like insulin-like growth factor 1 and negative regulators (e.g. adenosine monophosphate–activated protein kinase) of this pathway( Reference Katsanos, Kobayashi and Sheffield-Moore 33 , Reference Milner 34 ). AP contains essential amino acids, which trigger the aforementioned signalling pathways, enhancing protein accretion and LM( Reference Milner 34 ).

Only a few studies have examined the effect of protein source on body composition in older adults( Reference Houston, Nicklas and Ding 5 , Reference Sahni, Mangano and Hannan 6 , Reference Aubertin-Leheudre and Adlercreutz 9 ). In a study by Sahni et al. in men and women aged 59 (sd 9) years TP intake was 80 (sd 27) g/d in men and 76 (sd 26) g/d in women. In men and women, leg LM was higher in participants in the highest quartile of TP and AP intake compared with those in the lowest quartiles of intake( Reference Sahni, Mangano and Hannan 6 ). PP intake was not associated with LM in either sex. Although plant-based diets are low in certain essential amino acids, they have been linked with higher LM( Reference Pedersen and Cederholm 17 , Reference Han, Chee and Cho 35 ). Our data suggest accordingly that AP but not PP was associated with greater LM; however, PP was associated with increased aLM in the total population over 3 years of follow-up. Thus, the dietary protein quality (AP v. PP) intake in relation to health outcomes and LM needs to be further clarified.

Vitamin D can potentially affect LM through different mechanisms which are yet not fully elucidated( Reference Rizzoli, Stevenson and Bauer 14 , Reference Salles, Chanet and Giraudet 15 ). It has been suggested that vitamin D deficiency is linked with muscle weakness. The presence of vitamin D receptor in muscle tissue cells is yet a matter of debate( Reference Bischoff-Ferrari, Borchers and Gudat 13 , Reference Wang and DeLuca 36 ). Previous findings regarding the effect of vitamin D supplementation on LM are inconclusive( Reference Beaudart, Buckinx and Rabenda 11 , Reference Mithal, Bonjour and Boonen 12 ). A recent meta-analysis suggested that vitamin D has no significant effect on LM( Reference Beaudart, Buckinx and Rabenda 11 ). A separate investigation in the present data showed no significant effect of vitamin D (800 IU; 20 μg) and Ca supplementation on LM (M Isanejad, J Sirola, H Kröger and T Rikkonen, unpublished results). Furthermore, some evidence suggests that vitamin D and protein intake might have a synergic effect on increasing LM( Reference Salles, Chanet and Giraudet 15 , Reference Verreijen, Verlaan and Engberink 37 ). LM loss during ageing my partially be explained by the decreased ability of muscle to respond to anabolic stimuli provided by dietary protein through decreased MPS to physiological concentrations of amino acids and insulin( Reference Dardevet, Sornet and Bayle 38 ). Of particular interest, vitamin D deficiency was associated with insulin resistance in vivo ( Reference Combaret, Dardevet and Rieu 39 ), while vitamin D treatments have been linked to an increased expression of insulin receptor in skeletal muscle( Reference Salles, Chanet and Giraudet 15 , Reference Calle, Maestro and Garcia-Arencibia 40 ). The present study showed that the association of TP and AP with changes in LM and aLM was stronger in those women who received the vitamin D and Ca supplementation. Although there were no differences in the baseline characteristics between the intervention and control groups, it is possible that there were other modifying factors. To the best of our knowledge this was the first cohort study to evaluate the interaction between vitamin D and Ca supplementation and protein intake with LM and further studies are warranted.

Although data to support guidelines for weight loss in the elderly are limited, one of the main targets is the preservation of LM by adequate protein intake( Reference Mathus-Vliegen 16 ). Previously an intervention study has shown that a diet with high protein intake (35 % of energy) was associated with preservation of LM during weight loss( Reference Wycherley, Buckley and Noakes 41 ). Our data suggest that associations of TP intake and LM, aLM and trunk LM were significant in weight maintainers when weight changes do not confound. Therefore, these findings suggest that it is worth paying attention to the role of dietary protein intake in weight change among the ageing population.

The strength of the present study was that all the body composition measurements were available at baseline and over a 3-year period. We performed a careful adjustment for potential known confounders; however, there might be other factors that were not captured in this study. To adjust for body size as an important modifying factor for LM, a variety of methods have been used, and we chose baseline height which has been applied and used before( Reference Houston, Nicklas and Ding 5 , Reference Meng, Zhu and Devine 7 , Reference Kerr, Papalia and Morton 42 ). Worthy of note is that aLM provides a measure in which the component of muscle is relatively large.

A limitation of this study was that the study population consists of only elderly women and therefore caution should be taken when generalising the findings to elderly men. However, in previous studies when exploring associations between protein intake and LM, significant associations were observed similarly for men and women( Reference Houston, Nicklas and Ding 5 , Reference Sahni, Mangano and Hannan 6 ). It would be beneficial for future studies to explore the association of protein intake and LM change in both males and females. The 3-d dietary records method has been described as a suitable instrument for assessing energy and protein intake in elderly people( Reference Luhrmann, Herbert and Gaster 43 , Reference Paddon-Jones, Sheffield-Moore and Katsanos 44 ), which has been also used and applied to measure AP and PP intake( Reference Lord, Chaput and Aubertin-Leheudre 8 ). The latter study has also been validated against urinary nitrogen studies in both community-dwelling and institutionalised elderly people( Reference Paddon-Jones, Sheffield-Moore and Katsanos 44 ). However, errors in recording and change in dietary intake as well as type of protein intake are not avoidable, but the distribution of errors is unlikely to be related to the outcome. The dietary intake assessment was obtained only at baseline which may be insufficient to capture long-term dietary exposures. Information of intentionality of weight loss during the 3 years of follow-up was not available; therefore, it might be possible that those who lost weight over this period had generally lower inferior health condition as compared with weight maintainers or weight gainers. Lastly, causal associations cannot be obtained due to the observational nature of this study.

In conclusion, our findings support the current evidence that higher TP and in particular AP intakes are beneficial in preserving LM. A remarkable finding of this study was that the associations of TP, AP with increased LM were more apparent among elderly women who maintained their weight and received vitamin D and Ca supplementation. Since dietary protein intake, vitamin D and weight change are important health concerns of ageing, our results might underscore an important message for public health.

Supplementary material

To view supplementary material for this article, please visit http://dx.doi.org/10.1017/jns.2015.31

Acknowledgements

The OSTPRE-FPS was supported by the Finnish Cultural Foundation (Hulda Tossavainen Foundation; H. K.), the Sigrid Juselius Foundation (H. K. and T. R.), Academy of Finland (M. T.) and a Kuopio University Hospital EVO grant.

The authors declare no conflict of interests.

The authors’ responsibilities were as follows. M. I.: study design, analysis and interpretation of the data and drafting of the manuscript; A. T. E.: study design, analysis and interpretation of the data and critical revision of the manuscript; J. M. and J. S.: interpretation of the data and critical revision of the manuscript; H. K., T. R. and M. T.: critically revised the final manuscript for important intellectual content.

References

1. Muller, MJ, Geisler, C, Pourhassan, M, et al. (2014) Assessment and definition of lean body mass deficiency in the elderly. Eur J Clin Nutr 68, 12201227.CrossRefGoogle ScholarPubMed
2. Cruz-Jentoft, AJ, Baeyens, JP, Bauer, JM, et al. (2010) Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 39, 412423.CrossRefGoogle ScholarPubMed
3. Hughes, VA, Frontera, WR, Roubenoff, R, et al. (2002) Longitudinal changes in body composition in older men and women: role of body weight change and physical activity. Am J Clin Nutr 76, 473481.Google ScholarPubMed
4. Evans, WJ (2010) Skeletal muscle loss: cachexia, sarcopenia, and inactivity. Am J Clin Nutr 91, 1123S1127S.CrossRefGoogle ScholarPubMed
5. Houston, DK, Nicklas, BJ, Ding, J, et al. (2008) Dietary protein intake is associated with lean mass change in older, community-dwelling adults: the Health, Aging, and Body Composition (Health ABC) Study. Am J Clin Nutr 87, 150155.Google ScholarPubMed
6. Sahni, S, Mangano, KM, Hannan, MT, et al. (2015) Higher protein intake is associated with higher lean mass and quadriceps muscle strength in adult men and women. J Nutr 145, 15691575.CrossRefGoogle ScholarPubMed
7. Meng, X, Zhu, K, Devine, A, et al. (2009) A 5-year cohort study of the effects of high protein intake on lean mass and BMC in elderly postmenopausal women. J Bone Miner Res 24, 18271834.CrossRefGoogle ScholarPubMed
8. Lord, C, Chaput, JP, Aubertin-Leheudre, M, et al. (2007) Dietary animal protein intake: association with muscle mass index in older women. J Nutr Health Aging 11, 383387.Google ScholarPubMed
9. Aubertin-Leheudre, M & Adlercreutz, H (2009) Relationship between animal protein intake and muscle mass index in healthy women. Br J Nutr 102, 18031810.CrossRefGoogle ScholarPubMed
10. Paddon-Jones, D & Rasmussen, BB (2009) Dietary protein recommendations and the prevention of sarcopenia. Curr Opin Clin Nutr Metab Care 12, 8690.CrossRefGoogle ScholarPubMed
11. Beaudart, C, Buckinx, F, Rabenda, V, et al. (2014) The effects of vitamin D on skeletal muscle strength, muscle mass, and muscle power: a systematic review and meta-analysis of randomized controlled trials. J Clin Endocrinol Metab 99, 43364345.CrossRefGoogle ScholarPubMed
12. Mithal, A, Bonjour, JP, Boonen, S, et al. (2013) Impact of nutrition on muscle mass, strength, and performance in older adults. Osteoporos Int 24, 15551566.CrossRefGoogle ScholarPubMed
13. Bischoff-Ferrari, HA, Borchers, M, Gudat, F, et al. (2004) Vitamin D receptor expression in human muscle tissue decreases with age. J Bone Miner Res 19, 265269.CrossRefGoogle ScholarPubMed
14. Rizzoli, R, Stevenson, JC, Bauer, JM, et al. (2014) The role of dietary protein and vitamin D in maintaining musculoskeletal health in postmenopausal women: a consensus statement from the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO). Maturitas 79, 122132.CrossRefGoogle Scholar
15. Salles, J, Chanet, A, Giraudet, C, et al. (2013) 1,25(OH)2-vitamin D3 enhances the stimulating effect of leucine and insulin on protein synthesis rate through Akt/PKB and mTOR mediated pathways in murine C2C12 skeletal myotubes. Mol Nutr Food Res 57, 21372146.CrossRefGoogle ScholarPubMed
16. Mathus-Vliegen, EM & Obesity Management Task Force of the European Association for the Study of Obesity (2012) Prevalence, pathophysiology, health consequences and treatment options of obesity in the elderly: a guideline. Obes Facts 5, 460483.CrossRefGoogle ScholarPubMed
17. Pedersen, AN & Cederholm, T (2014) Health effects of protein intake in healthy elderly populations: a systematic literature review. Food Nutr Res 58, 10.3402/fnr.v58.23364.CrossRefGoogle ScholarPubMed
18. Karkkainen, M, Tuppurainen, M, Salovaara, K, et al. (2010) Effect of calcium and vitamin D supplementation on bone mineral density in women aged 65–71 years: a 3-year randomized population-based trial (OSTPRE-FPS). Osteoporos Int 21, 20472055.CrossRefGoogle Scholar
19. Jarvinen, R, Tuppurainen, M, Erkkila, AT, et al. (2012) Associations of dietary polyunsaturated fatty acids with bone mineral density in elderly women. Eur J Clin Nutr 66, 496503.CrossRefGoogle ScholarPubMed
20. Lohman, M, Tallroth, K, Kettunen, JA, et al. (2009) Reproducibility of dual-energy X-ray absorptiometry total and regional body composition measurements using different scanning positions and definitions of regions. Metabolism 58, 16631668.CrossRefGoogle ScholarPubMed
21. Kroger, H, Heikkinen, J, Laitinen, K, et al. (1992) Dual-energy X-ray absorptiometry in normal women: a cross-sectional study of 717 Finnish volunteers. Osteoporos Int 2, 135140.CrossRefGoogle ScholarPubMed
22. Erkkila, AT, Jarvinen, R, Karvonen, H, et al. (2012) Validation of a semi-quantitative FFQ using food records as a reference in older women in the Kuopio Fracture Prevention Study (OSTPRE-FPS). Public Health Nutr 15, 635639.CrossRefGoogle Scholar
23. Department of Health (editor) (1991). Dietary Reference Values for Food Energy and Nutrients for the United Kingdom. London: HMSO.Google ScholarPubMed
24. Goldberg, GR, Black, AE, Jebb, SA, et al. (1991) Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr 45, 569581.Google ScholarPubMed
25. Black, AE (2000) Critical evaluation of energy intake using the Goldberg cut-off for energy intake:basal metabolic rate. A practical guide to its calculation, use and limitations. Int J Obes Relat Metab Disord 24, 11191130.CrossRefGoogle ScholarPubMed
26. Willett, WC, Howe, GR & Kushi, LH (1997) Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr 65, 1220S1228S; discussion 1229S–1231S.Google ScholarPubMed
27. Visser, M, Harris, TB, Langlois, J, et al. (1998) Body fat and skeletal muscle mass in relation to physical disability in very old men and women of the Framingham Heart Study. J Gerontol A Biol Sci Med Sci 53, M214M221.CrossRefGoogle ScholarPubMed
28. Geirsdottir, OG, Arnarson, A, Ramel, A, et al. (2013) Dietary protein intake is associated with lean body mass in community-dwelling older adults. Nutr Res 33, 608612.CrossRefGoogle ScholarPubMed
29. Bauer, J, Biolo, G, Cederholm, T, et al. (2013) Evidence-based recommendations for optimal dietary protein intake in older people: a position paper from the PROT-AGE Study Group. J Am Med Dir Assoc 14, 542559.CrossRefGoogle ScholarPubMed
30. Nordic Council of Ministers (2014) Nordic Nutrition Recommendations 2012. Integrating Nutrition and Physical Activity, 5th ed. Copenhagen: Nordic Council of Ministers.Google Scholar
31. Suominen, MH, Jyvakorpi, SK, Pitkala, KH, et al. (2014) Nutritional guidelines for older people in Finland. J Nutr Health Aging 18, 861867.CrossRefGoogle ScholarPubMed
32. Eley, HL, Russell, ST, Baxter, JH, et al. (2007) Signaling pathways initiated by β-hydroxy-β-methylbutyrate to attenuate the depression of protein synthesis in skeletal muscle in response to cachectic stimuli. Am J Physiol Endocrinol Metab 293, E923E931.CrossRefGoogle ScholarPubMed
33. Katsanos, CS, Kobayashi, H, Sheffield-Moore, M, et al. (2006) A high proportion of leucine is required for optimal stimulation of the rate of muscle protein synthesis by essential amino acids in the elderly. Am J Physiol Endocrinol Metab 291, E381E387.CrossRefGoogle ScholarPubMed
34. Milner, RD (1969) Stimulation of insulin secretion in vitro by essential aminoacids. Lancet i, 10751076.CrossRefGoogle Scholar
35. Han, S, Chee, K & Cho, S (2015) Nutritional quality of rice bran protein in comparison to animal and vegetable protein. Food Chem 172, 766769.CrossRefGoogle ScholarPubMed
36. Wang, Y & DeLuca, HF (2011) Is the vitamin D receptor found in muscle? Endocrinology 152, 354363.CrossRefGoogle ScholarPubMed
37. Verreijen, AM, Verlaan, S, Engberink, MF, et al. (2015) A high whey protein-, leucine-, and vitamin D-enriched supplement preserves muscle mass during intentional weight loss in obese older adults: a double-blind randomized controlled trial. Am J Clin Nutr 101, 279286.CrossRefGoogle ScholarPubMed
38. Dardevet, D, Sornet, C, Bayle, G, et al. (2002) Postprandial stimulation of muscle protein synthesis in old rats can be restored by a leucine-supplemented meal. J Nutr 132, 95100.Google ScholarPubMed
39. Combaret, L, Dardevet, D, Rieu, I, et al. (2005) A leucine-supplemented diet restores the defective postprandial inhibition of proteasome-dependent proteolysis in aged rat skeletal muscle. J Physiol 569, 489499.CrossRefGoogle ScholarPubMed
40. Calle, C, Maestro, B & Garcia-Arencibia, M (2008) Genomic actions of 1,25-dihydroxyvitamin D3 on insulin receptor gene expression, insulin receptor number and insulin activity in the kidney, liver and adipose tissue of streptozotocin-induced diabetic rats. BMC Mol Biol 9, 65.CrossRefGoogle ScholarPubMed
41. Wycherley, TP, Buckley, JD, Noakes, M, et al. (2013) Comparison of the effects of weight loss from a high-protein versus standard-protein energy-restricted diet on strength and aerobic capacity in overweight and obese men. Eur J Nutr 52, 317325.CrossRefGoogle ScholarPubMed
42. Kerr, DA, Papalia, S, Morton, A, et al. (2007) Bone mass in young women is dependent on lean body mass. J Clin Densitom 10, 319326.CrossRefGoogle ScholarPubMed
43. Luhrmann, PM, Herbert, BM, Gaster, C, et al. (1999) Validation of a self-administered 3-day estimated dietary record for use in the elderly. Eur J Nutr 38, 235240.Google ScholarPubMed
44. Paddon-Jones, D, Sheffield-Moore, M, Katsanos, CS, et al. (2006) Differential stimulation of muscle protein synthesis in elderly humans following isocaloric ingestion of amino acids or whey protein. Exp Gerontol 41, 215219.CrossRefGoogle ScholarPubMed

Isanejad supplementary material S1

Isanejad supplementary material

File 62 KB

Altmetric attention score

Full text views

Full text views reflects PDF downloads, PDFs sent to Google Drive, Dropbox and Kindle and HTML full text views.

Total number of HTML views: 133
Total number of PDF views: 792 *
View data table for this chart

* Views captured on Cambridge Core between September 2016 - 23rd January 2021. This data will be updated every 24 hours.

Access
Open access
Hostname: page-component-76cb886bbf-fv2z2 Total loading time: 0.656 Render date: 2021-01-23T10:45:41.371Z Query parameters: { "hasAccess": "1", "openAccess": "1", "isLogged": "0", "lang": "en" } Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": false, "newCiteModal": false }

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Association of protein intake with the change of lean mass among elderly women: The Osteoporosis Risk Factor and Prevention – Fracture Prevention Study (OSTPRE-FPS)
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Association of protein intake with the change of lean mass among elderly women: The Osteoporosis Risk Factor and Prevention – Fracture Prevention Study (OSTPRE-FPS)
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Association of protein intake with the change of lean mass among elderly women: The Osteoporosis Risk Factor and Prevention – Fracture Prevention Study (OSTPRE-FPS)
Available formats
×
×

Reply to: Submit a response


Your details


Conflicting interests

Do you have any conflicting interests? *