Alessandro Laviano

Marc Reitman

Gustavo Abreu-Vieira

Patrick C Even
email: patrick.even@agroparistech.fr

Anne Blais

increased cost of Motor activity and heat Transfer between non-shivering Thermogenesis, Motor activity, and Thermic effect of Feeding in Mice housed at room Temperatureimplications in Pre-clinical studies

Keywords: mouse, indirect calorimetry, spontaneous motor activity, cost of activity, thermal regulation AMR, activity metabolic rate, RMR, resting metabolic rate, RQ, respiratory quotient, TEF, thermic effect of feeding, TMR, total metabolic rate

The components of energy expenditure, total metabolic rate (TMR), resting metabolic rate (RMR), thermogenic response to feeding (TEF), activity, and cost of activity were measured in fed and fasted mice housed at 22 and 30°C. Mice housed at 22°C had more than two times larger TMR and RMR. Mice at 22°C were less active when fasted but more active when fed. Cost of activity was nearly doubled in the fasted and in the fed state. Analysis of the short-term relation between TMR, RMR, and bouts of activity showed that, at 22°C, the bouts of activity induced a decrease in the intensity of RMR that reflected the reduced need for thermal regulation induced by the heat released from muscular contraction. This phenomenon induced a considerable underestimation of TEF and prevented its reliable measurement when mice were housed at 22°C. Correlation between TMR and activity measured across time in individual mice was very strong at both 22 and 30°C, but the correlation measured across mice was much weaker at 30°C and no longer significant at 22°C. We suspect that this phenomenon was due to the fact that RMR is a much more reliable predictor of TMR than activity. RMR is more variable at 22°C than at 30°C because of heat transfers between thermal regulation and heat released by other discontinuous processes, such as activity and TEF. Therefore, more noise is introduced into the correlations performed across multiple mice between TMR and activity at 22°C. On the other hand, it should be kept in mind that the doubling of TMR and RMR at 22°C is fueled by an increased non-shivering thermogenesis that can obviously modify how the mouse responds to pharmacological and nutritional challenges. Taken together, these results suggest that in pre-clinical studies, mice should be housed in conditions where thermal regulation is limited as is generally the case in humans. However, the increased sensitivity of mice to small changes in ambient temperature can also be used as a versatile tool to investigate the role of thermal regulation on the energy balance equation in humans.

inTrODUcTiOn Obesity research to get a mechanistic understanding and to provide guidelines for clinical investigations has used mainly mouse models for experiments that are not ethical in humans. No other animal model offers such large possibilities of phenotyping in response to metabolic, genetic, and behavioral manipulations [START_REF] Mcguinness | NIH experiment in centralized mouse phenotyping: the Vanderbilt experience and recommendations for evaluating glucose homeostasis in the mouse[END_REF]. However, it is important that mouse and human biology are similar in order to get reliable predictive values from mouse experiments. Energy balance is determined by the equilibrium between energy intake and energy expenditure from basal metabolic rate, thermic effect of feeding, cost of activity, and thermoregulation. In obesity research, it appears that the cost of thermoregulation was until recently an underestimated component despite the fact that it is widely acknowledged that in small endothermic rodents energy demand to maintain body temperature can become an important component of the energy Budget [START_REF] Cannon | Nonshivering thermogenesis and its adequate measurement in metabolic studies[END_REF]. In contrast, humans who have a mass about 3000-fold larger than mice live predominantly close to thermo-neutrality. Humans maintain their body temperature without thermoregulatory effort, the heat generated by ongoing metabolism is the only process needed. The mouse is very sensitive to ambient temperatures that decrease below thermal neutrality (28-31°C) because of its small size, and therefore very large body surface area to mass ratio. To maintain their body temperature, mice rely heavily on thermogenic processes specifically devoted to heat production, which are mainly uncoupled respiration in brown adipose tissue [START_REF] Desautels | Increased purine nucleotide binding, altered polypeptide composition, and thermogenesis in brown adipose tissue mitochondria of cold-acclimated rats[END_REF][START_REF] Enerback | Mice lacking mitochondrial uncoupling protein are cold-sensitive but not obese[END_REF], but also depend on shivering thermogenesis and heat generated by muscular activity [START_REF] Jansky | Non-shivering thermogenesis and its thermoregulatory significance[END_REF][START_REF] Overton | Phenotyping small animals as models for the human metabolic syndrome: thermoneutrality matters[END_REF].

In most cases, mice studies have been conducted at temperatures of 20-22°C, which is far below their thermal neutrality (30-32°C). This condition increases the cost of thermoregulation that can double energy requirements [START_REF] Abreu-Vieira | Integration of body temperature into the analysis of energy expenditure in the mouse[END_REF] and subsequently increases food intake, sympathetic activity, blood pressure, and heart rate. Therefore, the question is raised whether this large amount of energy produced to maintain body temperature can affect not only resting metabolism but also the amount and the cost of locomotor activity, the thermogenic response to feeding (TEF), and more generally the responses to various metabolic challenges. Indeed, the extra heat produced by the activity cost (physical work is only ~20% efficient) and TEF (enzymatic reactions are ~60% efficient) can potentially reduce the energy required for thermoregulation. Therefore, it is possible to consider that heat released by activity or feeding will reduce the cost of thermoregulation and can induce an underestimation of activity or feeding costs. This phenomenon was suggested in a previous paper which showed that TEE was correlated with activity when mice were housed at 30°C but not when they were housed at 20°C. At this lower temperature, energy expended from activity was masked by the reduction of the energy expended for thermoregulation [START_REF] Virtue | Below thermoneutrality, changes in activity do not drive changes in total daily energy expenditure between groups of mice[END_REF]. Moreover, evaluation of drug effects on energy expenditure may be altered when mice are housed at room temperature because the compensatory reduction in cold-induced thermogenesis can offset the drug-induced increase. It has been suggested also that when mice are housed below thermal neutrality, BAT thermogenesis may play an important role in food intake control and energy balance regulation [START_REF] Himms-Hagen | On raising energy expenditure in ob/ob mice[END_REF]. An inadequate response to cold was reported also in Lep ob /Lep ob mice [START_REF] Reichling | Attenuated cold-induced increase in mRNA for uncoupling protein in brown adipose tissue of obese (ob/ob) mice[END_REF], which may explain why it is only at temperatures below thermal neutrality that they have a lower energy expenditure than wild-type mice [START_REF] Trayhurn | Thermoregulation and non-shivering thermogenesis in the genetically obese (ob/ob) mouse[END_REF][START_REF] Wilson | Genetically obese C57BL/6 ob/ob mice respond normally to sympathomimetic compounds[END_REF].

According to these results, analysis of the preliminary results of a current study lets us suspect that ambient temperature could have profound effects on the mechanisms of adaptation of mice to low-protein diets. We extracted the control mice of this study to focus on the evolution of energy metabolism components when mice are acclimatized to the vivarium temperature (22°C) or at thermal neutrality (30°C). In this article, we report changes induced on resting and total metabolic rate (TMR), spontaneous motor activity, cost of activity, and the TEF.

MaTerials anD MeThODs animals and housing

Twenty-one female Balb/cOlaHsd mice were singly housed in a conventional facility with a reversed 12:12-h dark-light cycle (lights on at 20:00 hours). All experimental procedures complied with institutional guidelines and policies to prevent pain and distress under license from the French Veterinary Service (Ethics committee agreement number 12-095 and 13-012). The mice were provided by Harlan Laboratories (France) at 7 week of age and were allowed 2 weeks adaptation to the laboratory conditions before any experimental manipulation.

The mice used in this study were the control mice of two different experiments performed in 2014 and 2016. Water and food were provided ad libitum during the two studies unless otherwise stated. Mice were fed either a soy protein or a casein diet [by energy: soy protein or casein 24%, carbohydrate 66% (56.4% corn starch, 9.6% sucrose), fat (soy oil) 10%]. Food quotient of the two diets was 0.93. The results of the casein and soy-protein fed mice were pooled after we controlled for the similar reactivity of the two groups to the differences in ambient temperature.

In the first study (n = 11, 6 soy and 5 casein), the mice were housed continuously at 22°C. In the second study (n = 10, 5 soy and 5 casein), the mice were first housed at 22°C during 5 weeks, then the room temperature was increased to 30°C, and the mice maintained under these housing conditions for four more weeks (Figure 1).

indirect calorimetry

The indirect calorimetry system used in this study was a custom designed system working in pull mode and described in detail in several previous publications [START_REF] Even | Practical aspects of indirect calorimetry in laboratory animals[END_REF][START_REF] Even | Indirect calorimetry in laboratory mice and rats: principles, practical considerations, interpretation and perspectives[END_REF][START_REF] Even | Utilisation of the method of Kalman filtering for performing the on-line computation of background metabolism in the free-moving, free-feeding rat[END_REF]. Respiratory quotient (RQ) was calculated as the ratio of CO2 production (VCO2) over O2 consumption (VO2). Metabolic rate was calculated in watts (W) using the Weir equation [START_REF] Even | Indirect calorimetry in laboratory mice and rats: principles, practical considerations, interpretation and perspectives[END_REF]. Spontaneous activity was measured by force transducers located under the floor of the cage. Data acquisition and data processing were performed by computer programs developed in the laboratory and written in the LabVIEW ® .

In a first study, TMR and spontaneous activity (Act) were measured in ad libitum-fed mice housed at 22°C, and the TEF was measured at 30°C. In a second study, mice followed the reverse procedure, i.e., TEF was measured in mice housed at 22°C, and TMR and activity were measured under ad libitum conditions at 30°C after the mice were accustomed for at least 10 days to this temperature (Figure 1).

Measurement of TMr, rMr, and activity under Ad Libitum conditions

Mice were previously accustomed for 3-4 days to the calorimetry procedure by being housed in the same cages as used for the calorimetry recording. For the recording, they were kept in the same cage, and the cages were connected to the calorimetry system. VO2, VCO2, and intensity of spontaneous motor activity were recorded from five chambers (2.5 L volume, constant flow rate of 600 mL/min). Each chamber, then room air (to correct for background VO2-VCO2) was sampled during 100 s, so that each cage was sampled every 10 min. In the cages, a sheet of blotting paper was used as bedding. Water and food were freely available in small boxes fixed on the side of the chambers. Data acquisition was performed without interruption during 2 days. Day 2 was used for data analysis.

Analysis of the components of energy expenditure provided TMR and resting metabolic rate (RMR), RQ, and intensity of activity. The relation between TMR and activity was computed across time for each mouse. To improve the correlation between changes in the intensity of TMR and changes in the intensity of activity, a slight convolution of the activity signal was performed in order to reproduce the smoothing of the respiratory response induced by the dead space of the chambers (Figure 2A). RMR was obtained as the Y-axis intercept of the correlation between TMR and activity, and the cost of activity was computed as the slope of the correlation between TMR and activity (Figure 2B). The metabolic rate of activity (AMR) was computed as the difference between TMR and RMR.

The relations between TMR, AMR, and activity and TMR and RMR were also computed across multiple mice by using mean daily TMR, AMR, RMR, and activity values obtained in each mouse.

During experiment 1, temperature in the experimental room was regulated at 20°C in order to maintain a temperature of 21-22°C in the metabolic chambers. During experiment 2, mice were previously acclimatized for at least 1 week at a room temperature of 30°C, and temperature in the experimental room was maintained at 29°C in order to maintain a temperature of 30-31°C in the metabolic cages.

Measurement of the Thermic response to Feeding and of the short-Term changes induced by activity on TMr, rMr, and rQ during a cycle of Fasting and refeeding These measurements were performed by measuring VO2, VCO2, and spontaneous motor activity continuously on one single cage at 2 s intervals. The uninterrupted acquisition on one cage and the high frequency of data sampling were required to perform a detailed analysis of the short-term relation between changes in VO2 and VCO2 and intensity of activity in order to be able to precisely compute the energy cost of activity and subsequently to compute RMR and TEF without artifacts due to variability in spontaneous activity. This process is based on a filtering procedure according to the method of Kalman and has been described in detail in several previous publications from our laboratory [START_REF] Even | Indirect calorimetry in laboratory mice and rats: principles, practical considerations, interpretation and perspectives[END_REF][START_REF] Even | Utilisation of the method of Kalman filtering for performing the on-line computation of background metabolism in the free-moving, free-feeding rat[END_REF] and more recently in one by Van Klinken and colleagues [START_REF] Van Klinken | Estimation of activity related energy expenditure and resting metabolic rate in freely moving mice from indirect calorimetry data[END_REF]. Examples of results on individual mice are given Figure 3. Temperature in the cage was adjusted by decreasing room temperature below the required value in the cage and heating the wall of the cage with a heating coil controlled by a temperature gage. This system allowed the temperature (±0.2°C) to be maintained stable in the cage.

Mice were housed in the cage between 17:00 and 18:00 hours with water but no food and were kept overnight (i.e., mostly during their light period) in the metabolic cage (Figure 3). The next morning, a calibrated meal of 1 g (16 kJ) was introduced into the cage without interrupting data acquisition, and data recording was continued during 6-7 h. Average RMR and RQ during the 2 h that preceded the meal were used as baseline RMR and RQ values occurred between 23:00 and 08:00 hours, i.e., in fasted mice in the post-absorptive state and after non-shivering thermogenesis (NST) had time to switch off in mice housed at 30°C (see Figure 3). Hourly changes in the intensity of activity were also computed to compare intensity of spontaneous activity during fasting and refeeding. All experiments were performed in mice usually housed at 22°C. During experiment 1, temperature in the metabolic cage was regulated at 30°C; during experiment 2, temperature was regulated at 22°C.

statistical analysis

Data are presented as mean ± SEM. Values at 22 and 30°C were compared using a Student's t-test in Excel, or by two-way ANOVA in R ® when means were compared in relation to a third parameter (time for TEF, distribution classes for TMR activity, and RQ). Significant ANOVA results were followed using post hoc Tukey tests. Significance was set at P < 0.05.

resUlTs rMr, rQ, activity, and TeF in Fasted-refed Mice

Analysis of the changes in RMR and RQ during a cycle of fasting and refeeding showed large differences between mice housed at 22°C compared to those at 30°C. RMR measured after an overnight fast during the last 3 h before refeeding (~06:30-09:30) was nearly twice as large in mice housed at 22°C (Table 1; Figure 4A). Conversely, RQ was significantly lower attesting a greater reliance on fat derived substrates (Table 1; Figure 4D). During the fasting period (~23:00-10:00), activity was low and not significantly different at 30 and 22°C (Figures 3 and5).

Meal-induced increase in RMR was greatly reduced in mice housed at 22°C (Table 1; Figure 4B), and therefore, TEF computed by extrapolating pre-meal RMR appeared three times smaller [Table 1; Figure 4C;22°C(1)]. However, it appeared that post-meal RMR was lower than pre-meal RMR 4 h after the meal and onward, suggesting that during the post-prandial period, the extra heat released by activity and TEF decreased the extra-energy expended for thermal regulation. Therefore, computing TEF by extrapolating pre-meal RMR probably underestimated TEF at 22°C. If RMR measured 6 h after meal onset was used as baseline, then TEF at 22°C was similar to TEF at 30°C [Figure 4C

, 22°C(2)].
The meal-induced increase in RQ was of similar amplitude at 22 and 30°C but was of significantly shorter duration in mice housed at 22°C (Table 1; Figures 4E,F). After ingestion of the testmeal, and until the end of the experiment, spontaneous activity was significantly higher in mice housed at 30°C (Figures 3 and5).

relation between TMr, rMr, rQ, and activity Measured across Time in Fasted and Fed Mice

Fasted Mice

In mice housed at 30°C, the mean peak intensity of the bouts of activity was ~40 U and occurred 15 min after the onset of activity (Figure 6A). Mean duration of the activity periods was 30-40 min. The bouts of activity-induced parallel changes in the intensity of TMR, reflecting the metabolic cost of activity but only marginally modified the intensity of RMR. A very small but significant increase was however observed during the first min of activity [0.0347 ± 0.0037W, P < 10 -5 (+17% vs. baseline)].

At 22°C, the mean peak intensity of the bouts of activity was very significantly reduced down to one half of the intensity observed at 30°C (~20 U) (Figure 6B). Activity increased TMR but also profoundly affected the evolution of RMR: RMR increased very significantly during the first 5 min of activity [0.146 ± 0.013 W, P < 10 -16 (+ 37% vs. baseline)] then decreased progressively down to a value lower than before the onset of activity. The decrease lasted as long as the activity duration. After activity stopped, RMR increased progressively again and returned to pre-activity values in 30 min.

As we observed that the increase in TMR appeared of similar amplitude at 22 and 30°C despite the very significant decrease in the intensity of the bouts of activity, we calculated more precisely the cost of activity by processing the differences between RMR and TMR (δMR) in relation to activity (Figures 6C,D). This data processing confirmed that the cost of activity was higher at 22°C than at 30°C. The correlation between δMR and activity computed during the first 15 min of activity where the correlation was the best indicated a doubling of the metabolic cost of activity (Figure 6E).

As already quoted, RQ was significantly lower in mice housed at 22°C (Figure 6F) indicative of a greater reliance of fat derived energy. Activity induced transient changes of small amplitude that were similar at 22 and 30°C indicating that muscle contraction was fueled by the available substrate mix as used by the other tissues of the body.

Fed Mice

In fed mice, despite the fact that data acquisition was performed at a lower frequency and that the mice were fed, the correlations measured across time in each mouse between TMR and activity remained high (0.85 < R < 0.87) (Table 2, Figure 2B). This allowed the recording of fairly precise and reproducible values for RMR and cost of activity from the origin and from the slope of the correlations, respectively. TMR, RMR, and daily activity were significantly higher in mice at 22°C, and the cost of activity was approximately two times larger at 22°C than at 30°C (Table 2) as We observed a significant effect of activity on AMR at both 22 and 30°C (Figure 7A). However, activity did not significantly affect TMR at 22°C while the effect at 30°C was reduced and remained only borderline significant (Figure 7B). On the other hand, we observed a very strong correlation between TMR and RMR (Figure 7C), which may be related to the fact that RMR accounted for 68-74% of TMR (Table 2).

Distribution of TMr and rMr Values in Ad Libitum Fed Mice

Total metabolic rate and RMR values of ad libitum fed mice were more than doubled at 22°C (Table 2; Figure 8). This result is Unexpectedly, the distribution of RMR values at 30°C showed a peak at 0.15 W, i.e., at a value lower than RMR values measured after an overnight fast (Table 1), which suggests that at 30°C, under close to usual living conditions and despite continuous access to food, mice had possibly periods of very low metabolism.

Distribution of activity Values in Ad Libitum Fed Mice

Contrary to what was observed in food restricted mice, spontaneous activity was larger at 22°C when mice were fed ad libitum (Figure 9C). This increase relies on both more activity of high intensity (above 3 U, Figure 9A) and on the fact that, at 22°C, the mice were never quite completely restless and therefore had a much smaller peak of low activity values than mice at 30°C. The strong shift to the left, down to 0.4 AU, of the median activity intensity when mice were housed at 30°C shows that they were completely inactive half of the time. Accordingly, Figure 9B shows that the occurrence of activities of very low intensities (between 0 and 0.1) amounted to 38% of the time in mice housed at 30°C, while it was only 12% in mice housed at 22°C. In contrast, mice at 22°C exhibited increased occurrence of activities of intensities between 0.1 and 0.4 (27% of time vs. 12%, Figure 9B) testifying to a form of restlessness.

DiscUssiOn

This study confirms that energy expenditure is approximately doubled in mice housed singly at room temperature (22°C) vs. mice housed at thermal neutrality (30°C) [START_REF] Cannon | Nonshivering thermogenesis and its adequate measurement in metabolic studies[END_REF][START_REF] Ravussin | Effects of ambient temperature on adaptive thermogenesis during maintenance of reduced body weight in mice[END_REF]. The most significant results of this study are that (1) spontaneous activity in mice at 22°C is reduced when the mice have no access to food but increased when they are fed, (2) the energy cost of activity is doubled when the mice are housed at 22°C, (3) RMR is decreased during activity at 22°C, and (4) TEF is probably largely underestimated when measured at 22°C. Taken together, these results shed more light on how the energy expended with NST affects the components of energy expenditure and can undermine the use of mice housed below thermal neutrality as a model of human physiology.

spontaneous Physical activity

We observed that activity was reduced at 22°C when the mice were fasted, but increased when they were under ad libitum conditions. Activity reduction in fasted mice at 22°C was primarily due to a strong decrease in the intensity of the bursts of activity and not in a reduction in the number of activity periods (Figure 3 gives a typical example of this phenomenon). It was not possible to perform such a detailed analysis of the amplitude of the bursts of activity in ad libitum fed mice because data acquisition was performed in a multiplexed design and measurements were performed at 10 min instead of 2 s intervals. However, we observed that the average activity intensity in mice housed at 22°C was 30% higher than in mice housed at 30°C. In addition, a percent cumulative frequency analysis of the activity data [START_REF] Riachi | Percent relative cumulative frequency analysis in indirect calorimetry: application to studies of transgenic mice[END_REF] indicated that fed mice housed at 22°C spent less time fully inactive and more time restless or highly active. It is probable that the low ambient temperature made the mice fell less comfortable and induced fidgeting that decreased the time spent fully inactive.

On the other side of the distribution, the increased occurrence of high intensities of activity was probably related to the larger food intake induced by the increased energy requirements. Brown and colleagues previously reported that, in fasted rats, activity was reduced at room temperature (21°C) vs. thermal neutrality (28°C) [START_REF] Brown | Influence of mild cold on the components of 24 hour thermogenesis in rats[END_REF]. They reported that video recordings indicated a cold-defensive posture at 21°C in order to decrease convective and radiant heat transfer. In our study, we did not perform video recordings but it was visually obvious that fasted mice housed at 22°C were huddled up on themselves and were rather reluctant to move. The decrease in activity in fasted mice at 22°C can therefore be the result of a behavioral adaptation to the cold to reduce heat losses in conditions where they had no opportunity to access food and refill their energy stores [START_REF] Canals | Energetics and geometry of huddling in small mammals[END_REF]. In contrast, it seems that when under ad libitum feeding conditions, mice react to the decrease in room temperature by resting less, moving, and eating more.

We were not able to analyze properly the food intake recordings in this study, but we observed no decrease in BW in the mice housed at 22°C during the calorimetric studies (mean δBW 22°C = 0.19 ± 0.44), which implies that mice housed at 22°C ate approximately two times more than those housed at 30°C. In contrast, under ad libitum conditions, Kaiyala and colleagues ( 21) did not report any significant effect of temperature on spontaneous physical activity. The reason for this difference remains unclear. One possible explanation may be related to the fact that, because the difference in activity under ad libitum conditions relies on the lowest and largest activity levels, the less precise measurement of activity with red light-beams as used by Kaiyala and colleagues, vs. force transducers used here, may indicate that they missed these differences. However, the differences in TMR at 21 and 30°C was also smaller in the Kaiyala study than in this one, and therefore, the difference may also be due to the mouse strain or sex.

relation between activity, rQ, TMr, and rMr in Fasted Mice

Respiratory quotient was poorly affected by the occurrence of the bursts of activity at 22°C as well as at 30°C showing that muscle contraction was fueled by the available mixture of circulating glucose and fatty acids. Such lack of a specific increase in glucose oxidation and the strong correlation between activity and TMR probably reflects the fact that the bursts of activity were of low intensity and therefore that the work load on the muscles was low enough to be fueled by the current circulating mix of carbohydrates and lipids. The bursts of spontaneous activity induced a rapid doubling of TMR at both 30 and 22°C. This increase reflects the energy required to fuel muscular effort. In the experiments performed to measure TEF, the high rate of data acquisition combined with the data processing by the Kalman filtering [START_REF] Even | Practical aspects of indirect calorimetry in laboratory animals[END_REF][START_REF] Even | Indirect calorimetry in laboratory mice and rats: principles, practical considerations, interpretation and perspectives[END_REF][START_REF] Even | Utilisation of the method of Kalman filtering for performing the on-line computation of background metabolism in the free-moving, free-feeding rat[END_REF] allowed us to perform a very detailed analysis of the short-term changes between activity, TMR, and RMR in fasted mice. This analysis showed that activity marginally increased RMR at 30°C but induced curvilinear changes in RMR when the mice were housed at 22°C. At this temperature, RMR increased during the first 5 min then declined rapidly below the level measured before the onset of activity and finally reached a nadir at the end of the activity period. During the rest periods following the activity bursts, RMR returned to pre-activity values within ~30 min. The increase in RMR during the first 5 min of activity surprised us but was already described by Brown and colleagues [START_REF] Brown | Influence of mild cold on the components of 24 hour thermogenesis in rats[END_REF], although not as precisely as here, which supports the idea that this increase was not a computational artifact. It has been suggested that the temperature set-point may be increased during activity [START_REF] Abreu-Vieira | Integration of body temperature into the analysis of energy expenditure in the mouse[END_REF] possibly to heat muscles and to improve muscular work, which may explain why this phenomenon is observed with more intensity in mice housed at 22°C than in those housed at 30°C. The following decrease in RMR reflects obviously that the heat released by the working muscles reduced the cost of thermoregulation. Accordingly, when the mice stopped moving, the heat released from the muscles progressively decreased, therefore thermal regulation was progressively restored and RMR increased back to pre-activity values. This process was also suggested by Brown and colleagues in the rat [START_REF] Brown | Influence of mild cold on the components of 24 hour thermogenesis in rats[END_REF]. According to their calculations, the decrease in what they called "supplementary thermogenesis" lasted 1-1.5 h after the end of activity. The difference may be due to the inferred timing adjustment of their equations or because the measurement were done on rats in conditions where the cold stress induced a smaller response than what we report for mice in this study (heat production was increased by only 25% instead of 100% here). On the other hand, Kaiyala and colleagues [START_REF] Kaiyala | Acutely decreased thermoregulatory energy expenditure or decreased activity energy expenditure both acutely reduce food intake in mice[END_REF] reported that the thermoregulatory effort of mice housed at 21°C was reduced during the light period when activity and feeding were the highest.

The relation between the TMR increase above RMR (δMR) and the activity signal intensity computed from data acquired at a high rate showed a strong linear correlation between δMR and activity and indicated a doubling of the activity cost in fasted mice housed at 22°C. This result was confirmed in mice fed ad libitum where the correlation between TMR and activity, despite a less precise fit, unambiguously pointed to a significant increase of the activity cost at 22°C. Again, this phenomenon was already observed in rats by Brown and colleagues [START_REF] Brown | Influence of mild cold on the components of 24 hour thermogenesis in rats[END_REF] who reported that the increase in heat production induced by activity was of 0.040 vs. 0.068 J/min/g 0.67 at 28 and 21°C, respectively. Another study in which the cost of activity was investigated at different temperatures (7) also reported higher energy expended in the cold. The authors did not report directly the slope of the correlation between TMR and activity but in their discussion quoted that the energy cost per unit of activity was increased when mice were housed at low temperature (4°C). Therefore, the results of this study line up with previous reports showing that the cost of activity is increased when rats or mice are housed below thermal neutrality.

Abreu-Vieira and colleagues [START_REF] Abreu-Vieira | Integration of body temperature into the analysis of energy expenditure in the mouse[END_REF] suggested that this increase was likely due to increased heat loss from the less compact body position and disruption of the unstirred air layer around the body. However, from our data and in particular from the analysis of the very short-term changes between activity and TMR, we could observe that the extra cost of activity remained strongly correlated to the intensity of the activity signal, and therefore was produced in line with the ATP production for muscular contraction. In this context, the most plausible mechanism is an increased uncoupling between respiration and ATP production, possibly sustained by an increased expression of UCP2 and/or UCP3 in muscles to assist thermal regulation [START_REF] Schrauwen | UCP2 and UCP3 in muscle controlling body metabolism[END_REF]. It has been suggested already that variations in gene expression of UCP2 and UCP3 in muscles may affect the energy cost of exercise [START_REF] Schrauwen | Skeletal muscle UCP2 and UCP3 expression in trained and untrained male subjects[END_REF][START_REF] Buemann | The association between the val/ala-55 polymorphism of the uncoupling protein 2 gene and exercise efficiency[END_REF]. Abreu-Vieira and colleagues (7) also suggested that mice defend a higher body temperature during physical activity and that such increased uncoupling at 22°C may be a way to help increase muscle temperature. The reason for this uncoupling may be to warm the muscles and increase muscle performance at lower ambient temperatures [START_REF] Bennett | Thermal dependence of muscle function[END_REF]. Another parameter in favor of this interpretation is, as discussed at the beginning of this section, the transient increase in RMR observed during the first 5 min of activity periods at 22°C but not at 30°C. This could be interpreted as an increased heat production by NST to warm-up the muscles at the onset of muscular effort.

relation between activity, and TMr in Fed Mice

Despite the fact that, in free-feeding mice, the relation between TMR and activity measured across time in individual mice remained very strong at 22°C as well as at 30°C, and that the cost of activity at 22°C was approximately two times higher than at 30°C (as observed in fasted mice), we observed that when measured across multiple mice, the level of activity did not affect any more TMR in mice housed at 22°C and strongly weakened the relation between activity and TMR at 30°C. However, both at 22 and 30°C, AMR still strongly correlated with the amount of activity. These results are fully in line with those previously reported by Virtue et al. [START_REF] Virtue | Below thermoneutrality, changes in activity do not drive changes in total daily energy expenditure between groups of mice[END_REF] who observed in larger groups of mice (n = 27) that at 30°C both total-EE and activity-EE correlated with activity while, at 24°C, only activity-EE correlated with activity. To explain the fact that the relation between TMR and activity decreases (but generally remains significant) at 30°C and is no longer observed at 22°C, one must take into account that the main determinant of TMR is RMR. In this study RMR accounted for more than 70% of TMR and R 2 between TMR and RMR was above 0.90 at both temperatures. Therefore, it is not surprising that on a daily basis the activity effect on TMR be reduced by the variability in RMR, and finally vanishes below thermal neutrality where RMR fluctuates more as a result of heat transfer between thermal regulation and heat released by other discontinuous processes, such as activity and TEF. In addition, as seen when comparing Figures 2, 6 and 7, the range of TMR values available to fit the correlation with activity is much larger when measured across time in a single mouse than when measured between mice, which further weakens the correlation [see also Ref. [START_REF] Virtue | Below thermoneutrality, changes in activity do not drive changes in total daily energy expenditure between groups of mice[END_REF]].

Note that we performed this same analysis in fasted mice between 23:00 and 08:30 hours, i.e., when mice were in the postabsorptive state and adapted to the temperature in the metabolic cage. However, in these mice the level of activity was very low (Figure 5) and consequently individual TMR clustered around the mean group value (30°C, Mean 0.232, CV 8.93%, 22°C, mean 0.449, CV 7.48%). This prevented us from performing a precise analysis of the relation between TMR and activity across multiple mice and to reveal any effect of the activity level on TMR at 30°C as well as at 22°C (see Figure 10).

rQ, rMr, and TeF

Resting metabolic rate in fasted mice at 22°C was two times that at 30°C, a result in line with the increase reported previously in most studies [START_REF] Ravussin | Effects of ambient temperature on adaptive thermogenesis during maintenance of reduced body weight in mice[END_REF]. In contrast, the increase in RMR induced by ingestion of the test meal at 22°C, i.e., TEF, was only one third of the response observed in mice housed at 30°C. At first glance, this could be interpreted as a strong reduction in TEF in mice housed at 22°C but, taking into account the strong interplay between heat generation for thermoregulation and heat released by muscular contraction and TEF, it is highly probable that at 22°C, fasting RMR values decreased rapidly after meal ingestion. This was confirmed by the observation that at 22°C, post-meal RMR was lower than pre-meal RMR 4 h after the meal and onward. It was not possible to measure directly the time course of the decrease in RMR after meal ingestion, but if we refer to the fast pace of changes in RMR observed in response to bursts of activity, it is possible that the cost of thermal regulation decreased within minutes after the meal was given. Therefore, at 22°C, the RMR value measured after ingestion of the test-meal was the result of the increase in RMR induced by TEF and the decrease in NST induced by the heat released from activity and TEF. In these conditions, pre-meal RMR cannot be extrapolated to compute TEF whereas this extrapolation is possible at thermal neutrality when pre-meal RMR is equal to basal metabolic rate and cannot be further decreased. An argument supporting the hypothesis that in our experimental conditions NST was much reduced by the combined effect of activity and TEF is that, when TEF was computed in reference to RMR measured 6 h after the meal, we obtained TEF values similar to those measured at 30°C. Thus, in mice at 22°C, the standard method to measure TEF cannot be applied. In conditions where it is not possible to measure precisely the decrease in NST induced by activity and TEF, it must be acknowledged that TEF cannot be accurately measured in mice housed at 22°C. Respiratory quotient was significantly decreased after an overnight fast in mice housed at 22°C confirming that mice exhausted more quickly their glycogen stores and, after a few hours of fast had to rely on their lipid stores. The RQ response to feeding showed also that the overall increase in RQ was similar at 22 and 30°C, but that the increase was of shorter duration, reflecting the fact that mice housed at 22°C used more quickly the carbohydrates brought by the meal. Therefore not only the intensity of TEF but also the metabolic fate on the ingested nutrients is greatly affected by the increased energy demand of mice housed at 22°C. These significant differences in TEF and RQ responses to ingestion of a test-meal at 22 and 30°C should be considered carefully because when TEF and RQ are measured in humans, great care is taken to avoid any thermal stress.

limitations of This study

A main limitation in the interpretation of the results of this study is the lack of measurement of body temperature and caloric intake during calorimetry studies. The absence of caloric intake data was partly compensated for by the fact that we observed no significant changes in BW during the calorimetry studies at 22°C as well as at 30°C, indicating that energy balance was preserved and thus that caloric intake equaled total energy expenditure. In contrast, continuous online measurement of body temperature would have helped to verify that mice did not decrease their temperature set point at 22°C to reduce the cost of thermoregulation. This would have necessarily influenced the response to activity and feeding and would have provided a possible explanation for the increased cost of activity and fluctuations of RMR at 22°C. Comparison of gene expression in muscles and in white and brown adipose tissue of mice acclimatized at 22 and 30°C would have been helpful too, but in the study framework from which these data were extracted, the mice acclimatized to 30°C were reacclimatized to 22°C before organ and tissue collection.

cOnclUsiOn

In mice housed at 22°C, resting energy expenditure is doubled by NST to maintain thermal regulation, and the cost of activity is also doubled. Intensity of NST is highest at rest and is rapidly tuned down when extra heat is released from muscular contraction and feeding. In this context, the respective roles of basal metabolic rate, NST, activity, and thermic effect of feeding in the energy balance equation are very difficult to decipher. NST in humans is most of the time close to 0. If the mouse is intended to serve as a model of human physiological regulation, it may be reasonable to house them close to thermal neutrality, in particular when they are singly housed without bedding for measurements of metabolic and behavioral parameters. On the other hand, if housing temperature is used as a tool, the mouse can be a very interesting model to study the possible role of NST in the energy balance equation.

aUThOr cOnTriBUTiOns

PE and AB designed the study, performed the experiment, analyzed the data, and wrote the paper.

FUnDing

The study was funded with the resources of the laboratory. reFerences

Frontiers

  in Nutrition | www.frontiersin.org October 2016 | Volume 3 | Article 43

FigUre 1 |

 1 FigUre 1 | experimental design of the two studies.

FigUre 3 |

 3 FigUre 3 | example of results observed in response to ingestion of a meal-test after overnight (mainly during the light period for the mouse) food restriction (screen copies of the computer program developed in the laboratory to edit the calorimetry data). Top, mouse housed at 30°C (2014 study); bottom, mouse housed at 22°C (2016 study). VO2, VCO2, and activity data were initially recorded at 2 s intervals then processed by the method of Kalman to compute TMR and RMR. RQ was computed as VCO2/VO2. Vertical bars crossing the figures indicate time when the meal was introduced into the cage.

FigUre 2 |

 2 FigUre 2 | example of calculation of activity cost and rMr in mice under ad libitum conditions. Data were obtained from the multiplexed device. Acquisition was at 10 min intervals. (a) Changes in activity, TMR and RMR measured along the time. The original activity trace was slightly smoothed to better correlate with TMR. (B) Correlation between intensity of activity and TMR. Slope of the regression gives the cost of activity and origin gives RMR. RMR in (a) was computed as TMR (activity × cost).

FigUre 5 |

 5 FigUre 5 | hourly changes in the level of spontaneous activity (a) and mean activity values (B) before (pre-meal) and after (post-meal) delivery of the test-meal at 30°c (n = 11) and 22°c (n = 10). (a) Time effect, P < 10 -15 ; temperature effect, P < 10 -9 ; time × temperature effect, P < 10 -4 . (B) $, P < 0.01.

FigUre 4 |FigUre 6 | 7

 467 FigUre 4 | Meal induced changes in TMr, rMr (watts), and rQ in overnight fasted mice at 30°c (n = 11) and 22°c (n = 10). Test-meal (1 g, 16 kJ) given at t = 0. (a) Absolute TMR and RMR values, (B) TMR and RMR values relative to pre-meal values, (c) TEF computed as the cumulative increase in RMR over pre-meal values [30 and 22°C(1)] or after taking into account the possible decrease in RMR at 22°C [22°C(2)] [$: P < 10 -5 vs. 30 and 22°C(2)]. See TEF in kJ Table 1. Red dashed lines -extrapolation of fasting RMR at 30°C. Blue dashed lines -estimated decrease in RMR induced by activity and TEF used to adjust the calculation of TEF at 22°C [22°C(2)] (D) Absolute RQ values. Black dashed lines -food quotient (0.93). Green dashed lines -figures the RQ value of 1. (e) RQ values above 1 imply that part of the ingested carbohydrates is converted to lipids (lipogenesis). RQ changes relative to pre-meal RQ values, (F) Area under curve (AUC) computed as the cumulative changes in RQ over pre-meal values.

FigUre 7 | 8

 78 FigUre 7 | correlation between aMr and activity (a), TMr and activity (B), TMr and rMr (c) in ad libitum fed mice housed at 30°c (n = 9) and 22°c (n = 11). Data are adjusted to 20 g BW. Despite the fact that intensity of activity affects significantly AMR, the consequences on TMR are not significant. The strongest predictor of TMR appears to be RMR.

FigUre 8 |FigUre 9 | 9

 899 FigUre 8 | TMr (a) and rMr (B) values distribution adjusted to 20 g BW in ad libitum fed mice housed at 30°c (n = 9) and 22°c (n = 11). Vertical lines: mean (solid) and median (dashed). $: P < 10 -5 .

Frontiers

  in Nutrition | www.frontiersin.org October 2016 | Volume 3 | Article 43

FigUre 10 |

 10 FigUre 10 | correlation between aMr and activity (a), TMr and activity (B), TMr and rMr (c) in fasting mice housed at 30°c (n = 11) and 22°c (n = 10). Data were adjusted to 20 g BW. The small ranges of activity, TMR, and RMR values in fasting mice prevented results interpretation.

Frontiers

  in Nutrition | www.frontiersin.org October 2016 | Volume 3 | Article 43

TaBle 1 |

 1 components of energy expenditure in fasted-refed mice.

		30°c (n = 11)	22°c (n = 10)
		Mean ± seM	Mean ± seM	°c	Time °c × T
	Fasting	0.213 0.006	0.397	0.011	<10 -9	-	-
	RMR (W)
	Fasting	0.273 0.015	0.492	0.015	<10 -12	-	-
	TMR (W)
	TEF (kJ)	3.149 0.196	1.009	0.295	<10 -15	<10 -15 <10 -12
	TEF (%	19.68	1.22	6.309	1.845	<10 -15	<10 -15 <10 -12
	ingested)
	RQ	0.823 0.008	0.748	0.005	<10 -6	-	-
	AUC RQ	4.374 0.205	3.644	0.276	<10 -12	<10 -2	0.99

TMR and RMR values are adjusted to 20 g BW. AUC, area under curve. 5 Even and Blais Mice at 22 and 30°C Frontiers in Nutrition | www.frontiersin.org October 2016 | Volume 3 | Article 43

TaBle 2 |

 2

		Mean ± seM	Mean ± seM	P
	TMR (W)	0.244	0.024	0.686	0.020	<10 -9
	RMR (W)	0.167	0.018	0.510	0.016	<10 -10
	RMR (% TMR)	68.02	1.56	74.43	0.72	<10 -2
	Activity (AU)	0.945	0.095	1.463	0.102	<10 -2
	AMR (W)	0.077	0.007	0.175	0.006	<10 -8
	AMR (% TMR)	31.98	1.56	25.57	0.72	<10 -2
	Cost of act (W/AU)	0.083	0.008	0.123	0.007	<10 -3
	Cor. Coef. between	0.869	0.015	0.856	0.008	NS
	TMR and activity
	TMR and RMR are adjusted to 20 g BW. N = 9 instead of 10 at 30°C because
	recording of the activity signal failed on one cage.

components of energy expenditure in ad libitum fed mice. 30°c (n = 9) 22°c (n = 11)

Conflict of Interest Statement:

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Even and Blais. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or

reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.


Kada Klouche1
email: k-klouche@chu-montpellier.fr

Xavier Monnet

Alexander Zarbock3

Balanced solution versus saline in critically ill patients: a new piece to the puzzle!

Almost all critically ill patients receive intravenous fluids and this therapy is often the firstline treatment to optimize the hemodynamic condition. This common therapy is far from being innocuous. In particular, administration of large volumes of saline as resuscitation or maintenance fluid carries the risk of developing an hypernatremic and hyperchloremic metabolic acidosis, acute kidney injury, and might worsening patients' outcome [START_REF] Yunos | Association between a chloride-liberal vs chloride-restrictive intravenous fluid administration strategy and kidney injury in critically ill adults[END_REF]. The use of balanced solutions (BS) may avoid these adverse effects and would result in a lower rate of renal replacement therapy or persistent renal dysfunction than the use of saline [START_REF] Semler | Balanced crystalloids versus saline in critically ill adults[END_REF].

Recently, four large trials with controversial results evaluated the effect of balanced crystalloids versus saline on patient-centered outcomes in critically ill patients [START_REF] Semler | Balanced crystalloids versus saline in critically ill adults[END_REF][START_REF] Self | Balanced crystalloids versus saline in noncritically ill adults[END_REF][START_REF] Zampieri | Effect of intravenous fluid treatment with a balanced solution vs 0.9% saline solution on mortality in critically ill patients: the BaSICS randomized clinical trial[END_REF][START_REF] Finfer | Balanced multielectrolyte solution versus saline in critically ill adults[END_REF]. When fluid composition was monitored early before admission to the intensive care unit (ICU), the use of BS was beneficial [START_REF] Semler | Balanced crystalloids versus saline in critically ill adults[END_REF][START_REF] Self | Balanced crystalloids versus saline in noncritically ill adults[END_REF], but when this was monitored only after ICU admission, no difference could be demonstrated [START_REF] Zampieri | Effect of intravenous fluid treatment with a balanced solution vs 0.9% saline solution on mortality in critically ill patients: the BaSICS randomized clinical trial[END_REF][START_REF] Finfer | Balanced multielectrolyte solution versus saline in critically ill adults[END_REF]. In a secondary analysis of the multi-center, randomized BaSICS trial [START_REF] Zampieri | Effect of intravenous fluid treatment with a balanced solution vs 0.9% saline solution on mortality in critically ill patients: the BaSICS randomized clinical trial[END_REF] comparing balanced crystalloids with saline in critically ill patients, Zampieri et al. [START_REF] Zampieri | Association between type of fluid received prior to enrollment, type of admission, and effect of balanced crystalloid in critically ill adults: a secondary exploratory analysis of the BaSICS clinical trial[END_REF] were able to show that the patients who received balanced crystalloids before and after randomization had a reduced mortality compared to patients that only received saline.

In an article published in this issue [START_REF] Zampieri | Determinants of fluid use and the association between volume of fluid used and effect of balanced solutions on mortality in critically ill patients: a secondary analysis of the BaSICS Trial[END_REF], Zampieri and colleagues continued their investigation by carrying out a new post-hoc analysis of the original BaSICS study. They attempted to answer two questions: is the volume of fluid infused more determined by patient characteristics or local practices and is there a "dose-response" for the potential benefit provided by BS? They analyzed 10.505 patients, from 53 "effective" sites after lumping sites that recruited fewer than 20 patients. First, they found that basic predictors of filling, such as admission type, vasopressor use and heart rate, explained only a small part of the variance in fluid use during the first three days, whereas the site of enrolment explained it better. Second, and even more importantly, the results support a better prognosis with BS for septic patients who received more fluid, without being able to clearly define a thresh-old value. Accordingly, a benefit of BS was found for sites with high fluid administration, particularly for septic patients.

This study is the result of a secondary analysis of the BaSICS multicenter randomized trial, which included a large number of critically ill patients, enabling such an analysis. Over 5000 patients admitted to the ICU and over 3000 patients alive on day three were analyzed in each group. Thus, the results can be considered valid despite the fact that this is a post hoc study with multiple statistical manipulations.

The main finding of this study was the beneficial effect of BS over saline in septic patients when higher volumes were administered and is in line with a recently published clusterrandomized trial [START_REF] Semler | Balanced crystalloids versus saline in the intensive care unit the SALT randomized trial[END_REF]. The benefit of BS in septic patients has already been reported in secondary trial analyses [START_REF] Zampieri | Association between type of fluid received prior to enrollment, type of admission, and effect of balanced crystalloid in critically ill adults: a secondary exploratory analysis of the BaSICS clinical trial[END_REF][START_REF] Brown | Balanced crystalloids versus saline in sepsis. A secondary analysis of the SMART clinical trial[END_REF][START_REF] Jackson | Effect of early balanced crystalloids before ICU admission on sepsis outcomes[END_REF] and its dose-response effect suggested in a retrospective study [START_REF] Zampieri | Lactated ringer is associated with reduced mortality and less acute kidney injury in critically ill patients: a retrospective cohort analysis[END_REF]. The present study supports the idea that the benefit of BS is more potent in septic patients, and in case of large volumes infused. Indeed, the risk of hyperchloremic metabolic acidosis should appear only when such large volumes are infused, suggesting that the choice of fluid should be personalized depending on the amount of fluid that is required [START_REF] Backer | A plea for personalization of the hemodynamic management of septic shock[END_REF]. However, it is also possible that the infusion of smaller amounts of manifestation.

Typically, BS should be preferred to saline for hemodynamic stabilization in septic patients in whom the hypovolemic component of circulatory failure is strong, such as in case large fluid losses, peritonitis or pancreatitis, bearing in mind their detrimental effect in traumatic brain injury [START_REF] Semler | Balanced crystalloids versus saline in critically ill adults[END_REF]. It is perhaps because the comparison of BS vs. saline was not performed in such specific patients that large RCTs could not show any difference in mortality, as confirmed by a recent meta-analysis [START_REF] Beran | Balanced crystalloids versus normal saline in adults with sepsis: a comprehensive systematic review and meta-analysis[END_REF]. In any cases, it must be borne in mind that resuscitation with large volumes of fluid carries other risks than hyperchloremic acidosis and acute kidney injury. Whatever the type of fluid, fluid accumulation is clearly associated with worse outcomes, especially in septic patients [START_REF] Bakker | Current practice and evolving concepts in septic shock resuscitation[END_REF]. The present study focuses not only on the type of fluid used, but also on the volume infused.

In conclusion, the analysis published here adds a new stone to the edifice of resuscitation management in critical situations, but it should prompt further randomized studies for confirmation. This is not the final round, as the game continues.

Funding

This is a non-funded article.

Declarations

Conflicts of interest

KK and AZ declare no conflit of interest. XM is a member of advisory board of Cetinge and has received honoraria for giving lectures from Baxter and AOL.


Alexia Geny

Virginie Van Wymelbeke-Delannoy

Claire Sulmont-Rossé
email: claire.sulmont-rosse@inrae.fr

IMPACT OF FOOD-BASED FORTIFICATION ON NUTRITIONAL INTAKE AND STATUS IN OLDER PEOPLE: A META-ANALYSIS -PROTOCOL

Keywords: Aged, dietary intake, enrichment, malnutrition, body weight, systematic literature review objectives, data sources, study eligibility criteria, participants, and interventions, study appraisal and synthesis methods, results, limitations, conclusions

, setting the stage for a meta-analysis on the impact of DIY fortification on nutritional intake and status. Main eligibility criteria will include older adults aged ≥ 60 years living in various settings (at home, nursing home, hospital). Both randomized and non-randomized controlled trials will be considered. This meta-analysis aims to provide insights into the effectiveness of DIY fortification, offering a practical approach to enhance nutrition among older adults.

INTRODUCTION

Maintaining an adequate protein and energy intake in old age is an essential factor in preventing pathologies such as sarcopenia and undernutrition. Sarcopenia refers to the progressive loss of skeletal muscle mass that occurs with aging. Sarcopenia leads to a decline in muscle strength and function, resulting in reduced mobility and increased risk of falls and fractures [START_REF] Santilli | Clinical definition of sarcopenia[END_REF][START_REF] Cruz-Jentoft | Sarcopenia: revised European consensus on definition and diagnosis[END_REF]. Undernutrition encompasses a condition marked by insufficient intake of energy and essential nutrients leading to an imbalance between the body's nutritional needs and its actual supply [START_REF] Cederholm | ESPEN guidelines on definitions and terminology of clinical nutrition[END_REF]. While undernutrition can contribute to sarcopenia, it also extends to deficiencies affecting other organs and systems. Consequences of undernutrition extend beyond muscle health and may include weight loss, fatigue [START_REF] Azzolino | Nutritional Status as a Mediator of Fatigue and Its Underlying Mechanisms in Older People[END_REF], weakened immune function and higher susceptibility to infections [START_REF] Kawakami | Reduced immune function and malnutrition in the elderly[END_REF][START_REF] Alam | The immune-nutrition interplay in aging -facts and controversies[END_REF], cognitive impairment [START_REF] Knopman | Incident dementia in women is preceded by weight loss by at least a decade[END_REF][START_REF] Leblanc | Weight Trajectory over 20 Years and Likelihood of Mild Cognitive Impairment or Dementia Among Older Women[END_REF][START_REF] Lee | Association of anthropometry and weight change with risk of dementia and its major subtypes: A meta-analysis consisting 2.8 million adults with 57 294 cases of dementia[END_REF][START_REF] Feng | Malnutrition is positively associated with cognitive decline in centenarians and oldest-old adults: A crosssectional study[END_REF], increased risk and severity of chronic diseases [START_REF] Norman | Prognostic impact of disease-related malnutrition[END_REF], prolonged recovery times [START_REF] Shpata | The prevalence and consequences of malnutrition risk in elderly Albanian intensive care unit patients[END_REF], and increased mortality risk (Corti et al., 1994;[START_REF] Gentile | Malnutrition: a highly predictive risk factor of short-term mortality in elderly presenting to the emergency department[END_REF][START_REF] Sanchez-Rodriguez | Mortality in malnourished older adults diagnosed by ESPEN and GLIM criteria in the SarcoPhAge study[END_REF]. For a long-term perspective, sarcopenia and undernutrition threaten both daily functioning, autonomy and health of older people (Norman et al., 2020).

Research consistently underscores the critical role of protein and energy in maintaining muscle mass and preventing these adverse health outcomes among older adults [START_REF] Bauer | Evidence-based recommendations for optimal dietary protein intake in older people: a position paper from the PROT-AGE Study Group[END_REF][START_REF] Deutz | Protein intake and exercise for optimal muscle function with aging: recommendations from the ESPEN Expert Group[END_REF][START_REF] Volkert | ESPEN guideline on clinical nutrition and hydration in geriatrics[END_REF]. Despite its importance, several studies have revealed that protein and energy intake fall below recommended levels [START_REF] Lesser | Nutritional situation of the elderly in Eastern/Baltic and Central/Western Europe -The AgeingNutrition project[END_REF]. A review of protein intake in older adults in the UK shows that it falls below the recommendations for nutritionally vulnerable people. About a quarter of older women consume less than 45 g protein a day (Smith et al., 2022). A meta-analysis conducted by Ter not meet the daily allowance for protein. In the longitudinal SENECA study, 247 Danish and Dutch people aged 70-75 were first surveyed and re-examined 4-5 years later. Results showed a significant decline in energy intake for both genders over the four years of followup [START_REF] Schroll | Cross-cultural variations and changes in food-group intake among elderly women in Europe: Results from the Survey in Europe on Nutrition and the Elderly a Concerted Action (SENECA)[END_REF]. In France, [START_REF] Fleury | Home-Delivered Meals: Characterization of Food Intake in Elderly Beneficiaries[END_REF] showed that 83% and 72% of older people receiving home-delivered meals fail to meet the daily allowance for energy and protein, respectively. The average deficit between recommended and total intakes was 872 kcal and 33 g protein.

Given the prevalent shortfall in protein and energy intake observed among the older adults and the potential adverse effects associated with it, there is a clear need for interventions to support older adults in meeting their nutritional requirements. One promising solution is the implementation of food-based fortification strategies [START_REF] Morilla-Herrera | Effectiveness of food-based fortification in older people a systematic review and meta-analysis[END_REF][START_REF] Olson | Food Fortification: The Advantages, Disadvantages and Lessons from Sight and Life Programs[END_REF]. Food-based fortification involves enhancing the nutritional content of commonly consumed foods by adding essential nutrients (i.e. fortificants), in this case, focusing on protein and energy. This approach is designed to address nutritional deficiencies without significantly altering the volume of food to be ingested [START_REF] Has | Stratégies de prise en charge en cas de dénutrition protéino-énergétique chez les personnes âgées[END_REF]. While the food industry has introduced numerous fortified products, the concept of "do it yourself" (DIY) fortification (or home fortification - [START_REF] Olson | Food Fortification: The Advantages, Disadvantages and Lessons from Sight and Life Programs[END_REF] presents a unique opportunity for older adults and their caregivers to tailor nutritional enhancements to individual preferences and eating habits. Indeed, DIY fortification allows older individuals or their caregivers to incorporate essential nutrients into their regular meals. This flexibility is a notable advantage, for older adults who may face challenges in adopting changes to their consumption patterns.

Nevertheless, the concept of DIY fortification continues to be underknown and underused among older adults, caregivers and healthcare professionals. Research on this strategy is limited and scarce, further contributing to the lack of awareness and implementation (Trabal & Farran-Codina, 2015;[START_REF] Morilla-Herrera | Effectiveness of food-based fortification in older people a systematic review and meta-analysis[END_REF][START_REF] Douglas | The use of fortified foods to treat malnutrition among older adults: a systematic review[END_REF][START_REF] Mills | Can fortified foods and snacks increase the energy and protein intake of hospitalised older patients? A systematic review[END_REF].

Recently, [START_REF] Geny | Impact of food-based fortification on nutritional outcomes and acceptability in older adults: systematic literature review[END_REF] conducted a systematic literature review (SLR) of all studies related to the nutritional and acceptability aspects of DIY food-based fortification in older people. This review highlighted 137 distinct fortified recipes encompassing differences in the choice of food matrix (savoury and sweet), fortificants (regular food ingredients and macronutrient isolates or concentrates), and the additional load of protein and/or energy provided by fortified food compared to standard food. Building on this SLR, the current aim is to conduct a meta-analysis to assess the impact of DIY fortification on nutritional intake and status. This meta-analysis aims to provide a more quantitative and comprehensive understanding of the effects of DIY fortification, offering valuable insights into its potential contribution to improving nutrition.

MATERIALS AND METHODS

The protocol was drafted using the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols (PRISMA-P; [START_REF] Shamseer | Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation[END_REF]. The PRISMA checklist is presented in Supplemental Table 1. The protocol was deposited on PROSPERO with the registration number CRD42021244689.

PICOS question and eligibility criteria

We use a PICO framework for the formulation of our systematic review question [START_REF] Methley | PICO, PICOS and SPIDER: a comparison study of specificity and sensitivity in three search tools for qualitative systematic reviews[END_REF]. The differences between the eligibility criteria used in the systematic literature review [START_REF] Geny | Impact of food-based fortification on nutritional outcomes and acceptability in older adults: systematic literature review[END_REF] and the eligibility criteria used in the current meta-analysis are available on the Supplemental Table 2. For the current meta-analysis, the PICOS (Population, Intervention, Comparator, Outcome, Study design) eligibility criteria will be as follows:

Population. Any studies focusing on adults aged ≥60 years and any settings (home, nursing home, in hospital) will be relevant for inclusion. Older adults of all nutritional status, cognitive status and oral ability (e.g. chewing, swallowing) will be eligible for inclusion.

Studies carried out in the context of a specific pathological condition (e.g. cardio rehabilitation, renal failure, cancers, diabetes) will be excluded. Comparator. Eligible studies must include a DIY fortification intervention compared to either a control group or a control condition with no fortification (i.e., standard diet). Studies lacking a comparator will be excluded.

Outcome. Two categories of outcomes will be considered: (a) assessment of the nutritional intake (protein and energy intake), and (b) evaluation of nutritional status (body weight, screening questionnaires such as the Mini-Nutritional Assessment Questionnaire (MNA; Guigoz et al., 2002), and blood levels of albumin and pre-albumin).

Study design.

Randomized and non-randomized control trials will be eligible. All duration of follow-up will be eligible.

Other. No restriction will be set for the publication date. Only publications written in English will be included because of the uncertainty surrounding the words used to refer to the concept of "DIY food-based fortification" in foreign languages. Reviews, conference abstracts, editorials and grey literature will be excluded.

Search strategy

For the systematic literature review previously carried out by our laboratory [START_REF] Geny | Impact of food-based fortification on nutritional outcomes and acceptability in older adults: systematic literature review[END_REF], a search strategy with both thesaurus and free-text terms was developed after repeated attempts and adjustments to retrieve relevant articles in the following databases:

Web of Science (WOS), PubMed and Scopus (Supplemental Table 3). Separate title, abstract and keywords searches were conducted for older people, food-based fortification and outcomes in February 2021. A first update was performed in January 2022 [START_REF] Geny | Impact of food-based fortification on nutritional outcomes and acceptability in older adults: systematic literature review[END_REF]. A second update was performed in November 2023 for the purpose of the current meta-analysis. The reference lists of the included articles and those of relevant reviews will be screened manually for potentially relevant new articles.

Selection of articles

For the systematic literature review, the results for the three separate search strings were combined to identify relevant articles. After duplicates removal, article selection consisted of two screening phases. The first selection was based on title and abstract screening, and the second selection was based on a full-text screening. Screening was performed by two independent reviewers according to the inclusion and exclusion criteria. For each screening level, a training exercise was conducted before the starting of the screening process on a random sample of 100 titles and abstracts and 10 full texts to ensure high inter-reviewer reliability. Disagreements between reviewers were resolved by consensus or by consulting a third reviewer. This process led to the inclusion of 44 original studies [START_REF] Geny | Impact of food-based fortification on nutritional outcomes and acceptability in older adults: systematic literature review[END_REF]. For the current meta-analysis, an additional screening will be done by two independent reviewers (AG and CSR) according to the eligibility criteria defined for the current metaanalysis. Disagreements between reviewers will be resolved by consensus or by consulting a third reviewer (VVW). The list of excluded studies and the reasons of exclusion will be presented (Supplemental Table 4).

Study characteristics and data extraction

The following characteristics will be extracted from all included studies by two reviewers (AG and CSR), independently, with conflicts resolved by a third reviewer (VVW): Outcome data will be collected for each individual comparison as the mean, standard deviation (SD) and number of participants per group. When standard error or confidence intervals are reported, the SD values will be recalculated. When the group size is reported as a range, the smallest number of participants will be used for the meta-analysis in the interest of conservative estimates. In cases where data are presented graphically, data will be extracted in pixels using a digital screen ruler. In cases of missing data, corresponding authors will be contacted to provide missing data or original data. If no author contact details are available or if no response was obtained from the authors within three weeks after repeated contact, the data will be omitted from the meta-analysis. Outcome data will be extracted from all included studies by a first author (CSR), and a second author will check that the extracted data are consistent with information reported in articles (AG). Conflicts will be resolved after discussion, and extracted figures will be again checked for consistency.

Risk of bias assessment

A risk of bias grid was developed to accommodate both randomized and non-randomized trials and to account for the specificity of a nutrition trials. This grid was adapted from the , 2005). A first step aimed to identify the common risks of bias that are applicable regardless of trial design (e.g., classification of intervention, appropriateness of outcome measures, method to handle missing data, result reporting). A second step aimed to include criteria specific to randomization process (e.g., allocation concealment) and to non-randomized studies (e.g., appropriate control for confounding variables). The grid was tested on 10 articles randomly selected for the SLR [START_REF] Geny | Impact of food-based fortification on nutritional outcomes and acceptability in older adults: systematic literature review[END_REF] by two independent reviewers (CSR, VVW) and refined. The final grid includes 8 topics (Supplemental Table 5). Two reviewers will independently answer to all topic-related questions, each having four possible answers, "yes", "some concerns", "no" and "nonapplicable" (Critical Appraisal Skills Program, Long et al., 2020). Conflicts in assessment will be resolved by checking the article until agreement between the two reviewers.

Data analysis

Individual effect sizes. As included studies may report post-intervention value scores (randomized controlled trial, parallel group trial) or change-from-baseline value scores (prepost trial, crossover trial), individual size effects will be estimated by calculating Mean Difference (MD), according to Cochrane's recommendations [START_REF] Higgins | Cochrane Handbook for Systematic Reviews of Interventions version 6.4 Cochrane. Available from[END_REF]. In case of randomized controlled or parallel group trials, MD will be calculated by subtracting the fortified group post-intervention value from the control group post-intervention value. In case of pre-post or crossover trial, MD will be calculated by subtracting the fortified condition value from the control condition value. When articles contain more than one fortification condition (multi-arms trials), each comparison will be incorporated as an independent point estimate [START_REF] Higgins | Cochrane Handbook for Systematic Reviews of Interventions version 6.4 Cochrane. Available from[END_REF]. For example, in an article with one control group and two alternative fortification conditions (e.g., using two different fortificants), the two alternative fortification conditions will be compared to the same control group. For each outcome, the units will be as follows: Kcal for energy intake, g for protein intake, kg for body weight, g/l for albumin and pre-albumin.

Estimation of mean effect sizes. Meta-analyses will be performed using the metafor package in R [START_REF] Viechtbauer | Conducting Meta-Analyses in R with the metafor Package[END_REF] if at least five studies reported on a specific outcome. A randomeffects model will be chosen a priori, to account for between-studies differences such as design, fortified recipes and participant characteristics. In case of multiple-arm trials, the random factor "study" will be added to the model (argument slad in the rma function of the metafor package). Positive MDs will indicate an increase in the outcome measures after DIY fortification, whereas negative MD will indicate a decrease in the outcome measures. The significance level of the meta-analyses will be set at p<0.05. Heterogeneity will be assessed using the I2 statistic (Higgins et al., 2003). Exploratory sensitivity analyses will be conducted to evaluate results' robustness. First, subgroup analyses will be performed to check for potential issues with study design inclusion (i.e., exclusion of Non-Randomized Controlled trials; exclusion of within-subject design). Second, an analysis will be performed by excluding studies of potential high risk of bias. Finally, a meta-regression will be conducted on the effect of additional energy or protein load (i.e., the addition amount of energy or protein provided by a fortified food compared to a standard food) and the effect of setting (home, nursing home, hospital…) on the mean difference (argument mods in the rma function of the metafor package).

Publication bias. Funnel plots will be visually inspected for non-symmetrical distribution of standard errors around size effect. Funnel plot asymmetry will be tested using Egger's regression method [START_REF] Egger | Bias in meta-analysis detected by a simple, graphical test[END_REF]; function regtest of the metafor package). In addition, the 'trim and fill' method will be used to estimate the number of studies missing from the meta-analysis due to suppression of the most extreme results on one side of the funnel plot (function trimfill of the metafor package). This non-parametric method then augments the observed data so that the funnel plot is more symmetric, and recomputes the summary estimate based on the complete data to assess the sensitivity of the results to possible publication bias (Duval andTweedie, 2000a, 2000b).

RESULTS

The following results will be included in the final paper:

Table 3. Meta-analysis main results

This table will display result of the meta-analyses performed for each outcome. Specifically, this table will include:

-

The number of datasets

-

The mean effect size (MD, SD, p value)

-
The heterogeneity between studies (I 2 , p value)

-
The publication bias: (1) Egger's t, p value to assess funnel plot asymmetry;

(2) the number of missing studies and the mean estimate based on computed complete dataset to examine the sensitivity of the mean effect sized to publication bias ('trim and fill' method)

Figure 2. Forest plot

This figure will display forest plot for each outcome. Forest plots will provide a visual summary of the effect sizes and confidence intervals of individual studies, as well as the mean effect size and its 95% confidence interval.

Figure 3. Funnel plot

This figure will display funnel plots for each outcome. Funnel plots will include observed studies (solid circles) and imputed studies (empty circles).

Table 4. Sensitivity analysis

This table will display results of subgroup analyses to check for potential issues with study design inclusion or potential high risk of bias. For each subgroup analysis, this table will include:

-

The number of datasets -The mean effect size (MD, SD, p value)

-

The heterogeneity between studies (I 2 , p value)

DISCUSSION

Limitations of the Meta-analysis

A first limitation pertains to the inclusion of both randomized and non-randomized controlled trial. The systematic literature review which underpins the current meta-analysis revealed that slightly less than half of the studies assessing the impact of DIY fortification on nutritional outcomes had implemented RCTs (42% - [START_REF] Geny | Impact of food-based fortification on nutritional outcomes and acceptability in older adults: systematic literature review[END_REF]. One possible reason for the low number of RCTs is the complexity of implementing a fortified diet, especially in institutional or hospital settings. Indeed, it requires the active involvement and commitment of catering services to develop and produce fortified recipes. In practice, rather than a topdown approach in which researchers design a fortified food intervention under controlled conditions, the introduction of fortified foods is often initiated by catering services and/or health professionals. Researchers then collaborate to assess the consequences of this change, often in circumstances where it would be difficult to implement a randomised controlled trial. In fact, if an institution introduces a fortified food offer, the residents would find it very difficult to accept the fact that some of them would benefit from this offer while others would not, on the basis of a random draw. In addition, it can be difficult for catering services to offer a fortified diet alongside a standard diet. Although these studies present a higher risk of bias than the RCTs, it is worth including them in the meta-analysis because they test DIY fortification under real-life conditions. In addition, we can legitimately wonder whether the risk of bias linked to the preparation of recipes (repeatability of production processes, variation in the quality of final dishes) is not higher when it is initiated by a research team than when it comes from the institution's catering service.

A second limitation arises from the restriction of the search strategy to scientific literature in the English language. The challenge lies in the lack of a universally accepted terminology for expressing the concept of "fortification". As a result, we opted for a comprehensive search strategy employing a wide range of keywords. This approach initially yielded an extensive pool of over 10,000 articles, from which fewer than 50 articles were ultimately selected. This strategy proved successful by enabling the extraction of several pertinent articles not identified in previous systematic literature reviews that employed narrower search criteria (Trabal & Farran-Codina, 2015;[START_REF] Morilla-Herrera | Effectiveness of food-based fortification in older people a systematic review and meta-analysis[END_REF][START_REF] Douglas | The use of fortified foods to treat malnutrition among older adults: a systematic review[END_REF][START_REF] Mills | Can fortified foods and snacks increase the energy and protein intake of hospitalised older patients? A systematic review[END_REF]. However, because of time constraints, it was not possible to purse non-English publications or exploring the grey literature.

As a third limitation, it would have been better to have data extracted by two independent reviewers. However, upon an initial examination of studies included in the former systematic literature review, it became evident that there is considerable variability among these studies in terms of how they present data. This variability encompasses different formats (tables, text, figures), diverse estimators (e.g., mean, mean change, standard deviation, standard error, 95% confidence interval, t-value, p-value), and varied units (e.g., kJ or kcal for energy intake). Given this complexity, a more efficient and secure approach emerged: one reviewer will be responsible for extracting relevant data from each paper and conducting the necessary calculations to derive means and standard deviations for each group or condition. A second reviewer will then independently verify the process and recomputed the calculations to identify any errors. Finally, both reviewers collaboratively conducted a third check (one reviewer will read the paper, while the other will check the data file) to identify any potential typographical mistakes. As a recommendation for future primary studies, it is advisable to present data in a standardized and straightforward manner (e.g., a table that includes the mean and standard deviation for each group or condition at each measurement time).

INTRODUCTION

METHODS

Protocol and registration 5

Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.

Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.

Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

Study selection 9

State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).

Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

Data items 11

List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.

Risk of bias in individual studies 12

Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

DISCUSSION

Summary of evidence 24

Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).

Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).

Conclusions 26

Provide a general interpretation of the results in the context of other evidence, and implications for future research.

FUNDING

Funding 27 Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review.

Supplemental Table 3. Search strategy in Web of Science, PubMed and Scopus. (For PubMed, MeSH terms are in bold).

Concept Key-words

Old people "aged" OR "elderly" OR "older" OR "senior" OR "aging" OR "ageing" AND Food-based fortification "food, fortified" OR "enriched food" OR "enriched foods" OR "food enrichment" OR "diet enrichment" OR "enriched diet" OR "enriched diets" OR "food fortification" OR "supplemented food" OR "supplemented diet" OR "supplemented diets" OR "food supplementation" OR "diet supplementation" OR "additional food" OR "additional foods" OR "added food" OR "fortified drink" OR "fortified beverage" OR "enriched drink" OR "enriched beverage" OR "enriched beverages" OR "dense food" OR "dense foods" OR "dense diet" OR "dense diets" OR "food, formulated" OR "formulated food" OR "fortified foods" OR "dietary enrichment" AND Outcomes Nutritional intake: "eating" OR "food intake" OR "dietary intake" OR "feed intake" OR "food consumption" OR "diet pattern" OR "dietary pattern" OR "nutritional intake" OR "protein intake" OR "energy intake" OR "nutritional requirement" OR "nutritional requirements" OR "dietary protein" OR "dietary proteins" OR "feeding" OR "feeding behavior"

OR Nutritional status: "nutritional status" OR "body weight" OR "weight" OR "Body Mass Index" OR "BMI" OR "muscle mass" OR "malnutrition" OR "undernutrition" OR "undernourished" OR "malnourished" OR "appetite" OR "sarcopenia" OR "frail elderly" OR "frailty" OR "frail" OR "elder nutritional physiological phenomena"

Intervention.

  Only interventions exclusively testing DIY fortification in energy and/or protein will be eligible. Excluded from the review are: (a) interventions combining DIY food-based fortification with another enrichment strategy (e.g., Oral Nutritional Supplements (ONS)), and (b) intervention using fortified food products developed and marketed by the food industry.

-

  First author name, publication date, funding sources -Experimental design -Population: age, gender, setting -Description of DIY fortification solutions: food matrices, fortificants, additional energy and/or protein load provided by fortified food -Description of control condition -Intervention period duration -Outcomes and method of measuring outcomes

  tools proposed by Cochrane (Risk-of-Bias tool for randomized trials, RoB 2: Sterne et al., 2019; Risk Of Bias In Non-randomized Studies -of Intervention tool, ROBINS-I: Sterne et al., 2016), the Critical Appraisal Skills Programme (CASP, 2021) and the American Dietetic Association Quality Criteria Checklist (ADA

Figure 1 .

 1 Figure 1. PRISMA Flowchart

  for the review in the context of what is already known. Objectives 4 Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).

Table 1 . Characteristics of the articles included in the meta-analysis.

 1

	This table will display the characteristics for all included studies:
	-	First author name, publication date
	-	Experimental design
	-	Population: age, gender, setting
	-	Description of DIY fortification solutions: food matrices, fortificants, additional
		energy and/or protein load provided by fortified food
	-	Description of control condition

Table 3 . Risk of bias

 3 This table will present the risk of bias for all included studies.

  any assessment of risk of bias across studies (see Item 15). additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]).

	Summary measures	13	State the principal summary measures (e.g., risk ratio, difference in means).
	Synthesis of results	14	Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I each meta-analysis.	2 ) for
	Risk of bias across studies	15	Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).
	Additional analyses	16	Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.
	RESULTS
	Study selection	17	Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
	Study characteristics	18	For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
	Risk of bias within studies	19	Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12).
	Results of individual studies	20	For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.
	Synthesis of results	21	Present results of each meta-analysis done, including confidence intervals and measures of consistency.
	Risk of bias across studies Present results of Additional analysis 22 23 Give results of
	From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(7):
	e1000097. doi:10.1371/journal.pmed1000097

FUNDING STATEMENT

This work received funding by the French "Investissements d'Avenir" program, project ISITE-BFC (contract ANR-15-IDEX-0003) and from ANR (ANR-20-HDHL-0003 FORTIPHY), Research Council Norway (RCN 321819), BBSRC (BB/V018329/1) under the umbrella of the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL) and of the ERA-

CONFLICT OF INTEREST

The authors have no conflict of interest to declare for the present manuscript. During the past 36 months, CSGA and CHU Dijon received research grants from OGUST, SAVEURS et VIE and INSTITUT NUTRITION; Claire Sulmont-Rossé received consulting fees from BEL FOOD and author fees from Correspondances en Métabolismes Hormones Diabètes et Nutrition.

ETHICAL STATEMENTS

Not applicable (Systematic Literature Review and Meta-Analysis).

AKNOWLEDGEMENT

The authors thanks David Makowski, INRAE, MIA for his precious advices on statistical analysis. 1. PRISMA checklist.

AUTHOR CONTRIBUTION

Alexia

Supplemental Table

To be completed in the final paper. 2. Eligibility criteria of the current meta-analysis versus eligibility criteria of the systematic literature review [START_REF] Geny | Impact of food-based fortification on nutritional outcomes and acceptability in older adults: systematic literature review[END_REF].

Supplemental Table