Effect of Behavioural Model-Guided Nutritional Counselling on Old Age People’s Nutritional Status: A Quasi-Experimental Study Design

doi:10.21203/rs.3.rs-2569547/v1

Background: Physiological, pathological, and socioeconomic changes occur in older people that could influence their dietary intake, efficiency of nutrient utilization, and nutritional status. Impaired nutritional status aggravates existing disease conditions and worsens their health problems. Appropriate nutrition assessment followed by timely intervention and regular follow-up improves the nutritional status and health outcomes of older people, which are lacking in Ethiopia. Therefore, this study was aimed to estimate the effect of behavioural model-guided nutritional counselling on older people’s nutritional status in Bahir Dar City, Northwest Ethiopia.

Methods: A single-group pretest-posttest quasi-experimental design was conducted on 293 community-dwelling older adults aged 60 and above from January 28 to May 26, 2022. Trained nurses provided nutritional counseling guided by the health belief model and the theory of the behavioural model. The intervention was through home-to-home visits once a week for one month, with a two-month follow-up. Nutritional status, nutritional knowledge, dietary intake, body weight, and body mass index were measured. All measurements were recorded on a pre-post schedule, and the changes in outcomes were measured using a paired T-test.

Results: About 34(12.5%) and 21(9.6%) of the study participants were malnourished, while only 87(32.1%) and 76 (34.7%) were normal before and after the intervention, respectively. The mean score of nutritional status significantly increased from 21.55 ± 3.72 before the nutritional intervention to 21.64 ± 4.12 after the intervention (x̄ = -0.30, t₂₁₈ = -2.72, 95% CI: -0.52- (-0.83), p = 0.007). While, mean body weight and the body mass index did not change after the intervention’s adoption.

The mean nutrition knowledge score rose from 7.58 ± 1.05 to 11.61 ± 1.37 (x̄ = 3.98, t₂₁₈ = -32.79, 95% CI: -4.21-(-3.73), p < 0.001). Furthermore, the consumption of dairy products, fruits, and meat or egg intake increased after the intervention (p < 0.001).

Conclusion: Behavioural model-guided nutritional counseling improved the nutritional status of community-dwelling older people. A participant-centered nutritional programme recommended improving the health of community-dwelling older people.

Trial Registration: Clinical Trial Registration-URL: www.clinicaltrials.gov, identifier number: NCT04746664, first released 10/02/2021.

Behavioural model

Old age people

Nutritional status

Nutrition counselling

Dietary practice

Ethiopia

Physiological, pathological, and socioeconomic changes occur in old age people that could influence their dietary intake, efficiency of nutrient utilization, and nutritional status (1, 2). Malnutrition in old age people basically addressed through periodic assessment and individualized treatment plans (3). Moreover, individualized dietary counselling—a method by which people are guided and helped to put healthy foods and lifestyles into practice—is more effective than similar advice given for all old age people as they greatly vary in terms of biological age, disease conditions, functional frailty, and nutritional status (4).

According to studies, nutritional counselling is a crucial tool for maintaining good health and is a recognized component of the treatment of eating disorders (4, 5). A recent review study showed nutritional counselling for malnourished older people had a positive impact on their body composition, weight, and grip strength (6). Furthermore, theoretical or behavioural models such as the health belief model (HBM) and theory of planned behaviour (TPB) guide nutritional interventions that are more effective in encouraging behavior change than those that are not (7, 8). The Academy of Nutrition and Dietetics also advises health practitioners to employ a theoretical strategy as described in the Nutrition Care Process (NCP)(9).

In Africa, however, there is a shortage of information as well as epidemiological data on the nutritional status and intervention outcomes of the ageing population (10, 11). Furthermore, nutritional interventions in sub-Saharan Africa do not target older people (12), and, equally, the traditional support from families and communities has declined largely due to widespread poverty, urbanization, and globalization (11).

Similarly, demographic growth and population ageing are occurring in Ethiopia in the absence of adequate economic and infrastructure systems (10). Available studies in the country reported a 10.33% (13) to 28.3% (14) prevalence of malnutrition among the old age people. Yet, there is a lack of research examining the advantages of tailored dietary counselling for the Ethiopian old age population. Therefore, the purpose of this study was to examine the effect of behavioural model-guided nutritional counselling on old age people’s nutritional status.

Study design and period

A single-group pretest-posttest quasi-experimental design was conducted in Bahir Dar City, Northwestern Ethiopia. Since there is no usual nutritional care system for old age people in Ethiopia, it was unethical to include a control group that would have received no dietetic intervention, as nutritional care should be provided to those in need (15). The baseline survey was conducted from January 28 to February 8, 2022; the nutrition counselling intervention was implemented from February 14 to March 15, 2022; and the end-line survey was conducted from May 16 to 26, 2022.

Study population

This study included community-dwelling old age people aged 60 and above who lived at least six months in the selected kebeles (the smallest administrative unit in Ethiopia) and desired to live three months in the area. We excluded old age people who used therapeutic dietary supplements and those who were seriously ill.

Sample size and sampling procedure

The sample size was calculated following the sample size for the before-after study or paired T-test (16) with the assumption of a 95% confidence level, 80% power, 20% effect size, and one arbitrary standard deviation of the change in the outcome since no previous study was found in Ethiopia. The final sample size was 323 after accounting for 1.5 design effects and 10% lost to follow-up.

A multi-stage cluster sampling technique was used to address the study participants. Since Bahir Dar City Administration has six sub-cities, and two of them (Belay Zeleke and Gish-Abay) were used for previous studies, two other sub-cities, Tana and Dagmawi Minilik, were selected using a simple random sampling method in the first stage. In the second stage, two clusters of Kebeles, the smallest administrative unit in Ethiopia, were selected from each sub-city using the lottery technique. Lastly, all eligible old age people found in the selected kebeles were contacted in a home-to-home visit. If the targeted household was closed, a second visit was conducted. If the household was not open again, it was left unattended and taken as a non-respondent. When there was more than one eligible person in a household, one participant was chosen by a random lottery method.

Intervention approach

Individual-based nutritional counselling guided by a combination of the health belief model (HBM) and theory of planned behaviour (TPB) was implemented. The counselling package was adapted from previous studies on older people in other countries (17, 18). The intervention programme was a personalized intervention involving 45 to 60 minutes face-to face sessions conducted to home-to-home-visit once per week for one-month period, and weekly individual home-to-home visit follow-up for two months. Eight trained nurses provided the nutritional counselling and a convenient day and time were selected in discussion from all seven days of the week. The main message was written on flyers in the local language (Amharic) and given to each study participant as a reminder to lead a healthy lifestyle. Any family member or neighbour was asked to read the flyer to the elderly and/or other family members on behalf of those who could not read.

The objective of the intervention was not to completely change the participants’ or family’s food habits, but to correct possible shortfalls in their diet based on the food items that they are familiar with and that are already part of their daily diet. The main intention was to increase awareness of the importance of a balanced diet intake; improve the regularity of food intake (three major meals as breakfast, lunch, and dinner) with the addition of snacks between them; increase consumption of food varieties, especially fruits and vegetables, whole grains, and protein-rich foods without avoiding any specific foods except in medical cases; drink at least eight glasses of water; consume fewer foods with sodium, added sugar, saturated fat, or refined grains; and control the amount of noncaloric beverages consumed per day.

Intervention fidelity

A checklist of criteria was constructed to evaluate the fidelity of the intervention based on the best practice recommendations of the National Institutes of Health Behavior Change Consortium (NIHBCC) framework (19). The checklist tried to evaluate the intervention design, training of counselors, counselling delivery, receipt of counselling, and enactment of knowledge and skills gained from the intervention.

The intervention design was supported by theoretical models. To standardize the procedure, each study participant had the same number and frequency of counselling sessions, and the minimum lengths of contacts were comparable. The counsellors were trained in groups using a standardized training manual, role plays, and simulations of consulting practice, followed by feedback to the provider using performance criteria. Moreover, a written pre-post-training test was utilized to evaluate the counsellors’ knowledge and skill acquisition. A minimum of 80% was accepted, and those who scored below this were given remedial training.

The principal investigator monitored the counselling delivery process. They coached and evaluated randomly selected consulting sessions for each counselor. The evaluator used a "yes/no" rating system to check items such as the use of the counselling guide, the provision of all the content, the duration and frequency of the counselling, and the ability to answer questions correctly. Feedback was given to the counselors after each assessment to improve the observed gaps. The homework tasks were set at the end of each session to reflect the discussions in that session, and the counselor reviewed them in the following lesson. The reasons for not completing homework were explored, as these reasons may indicate a lack of understanding or hinder the implementation of learning skills.

In addition, the intervention’s enactment or implementation of knowledge acquired from the intervention was assessed through participants’ self-report. The study participants were interviewed about the change in their dietary intake, meal frequency, and variety following the nutrition consultations. Besides, counselors recorded participant attendance and self-reported knowledge measures at the end of counselling session. Those old age people who did not attend all consultation sessions were considered to "not adhere to the guideline", while those who dropped out of the study were considered to be "lost to follow-up".

Furthermore, the participant satisfaction survey was taken after a week. Finally, at the end of three months, participants were questioned with eight open-ended questions created by the researchers to learn how they felt about the program in terms of its scope, fidelity, the length of the counselling sessions, and whether or not their personal expectations were realized.

Data collection instruments and procedures

Data were collected in pre- and post-tests using structured, interviewer-administered questionnaires and anthropometric measurements. The wealth index was assessed based on household assets, household water source, and latrine condition adapted from the Ethiopian Demographic Health Survey (EDHS)(20). Food access was examined through the Household Food Insecurity Access Scale (HFIAS) (21), which has been previously utilized in Ethiopian studies (22, 23). If the aged person is living with others, household head females were the respondents for this part since they are culturally responsive to handling household food consumption (24).

The nutritional status was measured using a validated Mini Nutritional Assessment tool, while the dietary practices were evaluated using the 24-hour dietary recall (24HDR), meal frequency, and dietary diversity score methods. Furthermore, a True-False or I do not know questionnaire was utilized for general nutritional knowledge questions (GNKQ), and a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) was utilized to measure the health belief model (HBM) and theory of planned behaviour (TPB) constructs.

Wealth scores were created to classify households as the poorest, poor, middle, rich, and richest (20). Each respondent received a total score for food access that ranged from 0 to 27, with higher scores indicating greater food insecurity or inaccessibility and vice versa (21). The 16 food items of 24HDR were merged into eight mutually exclusive food groups to find foods with similar nutritional profiles (25). Consumption of each food group item was given one point, and a diet of at least four dietary diversity scores (DDS) was taken as nutritionally adequate, otherwise inadequate (25, 26) for the total number of foods consumed per day.

The nutritional status is given a maximum of 30 points and is classified as malnourished (< 17), at-risk (17-23.5), or well-nourished (≥ 24). For the 18 items of the general nutritional knowledge questionnaire (GNKQ), each correct answer got one point, and each incorrect answer and “I do not know” got zero. The scoring was reversed for items that represent misinformation. The constructs of HBM and TPB were measured by the mean score of a five-point Likert scale. There were six BSc nurses and six urban health extension workers as data collectors, and a master nutritionist together with the investigators served as supervisors. Besides, another eight experienced BSc nurses were enrolled as intervention counselors.

Data processing and analysis

The data were entered into EpiData version 3.1 (27) and exported to SPSS version 23 (28) for data cleaning and analysis. Descriptive statistics for categorical data were expressed in frequencies and percentages, whereas mean and standard deviation (SD) were used for continuous data. The effects of the intervention on outcomes were evaluated using a paired t-test. All assumptions were checked before each test, and a P-value of less than 0.05 was considered statistically significant.

Data quality management

The study was registered at the Clinical Trial Registration (29) with identifier number NCT04746664 and the transparent reporting of evaluation with nonrandomized designs (TREND) (30) guideline was used for the reporting of the results. Furthermore, both before and after intervention measurements were conducted using the same set of materials. Anthropometric guidelines and recommendations (31, 32) as well as COVID-19 precautions, were strictly followed. The data collectors and supervisors team took two days of training on the study’s purpose and the utilization of data collection tools. Though randomization and masking were not carried out due to the nature of the study, participants, counselors, and data collectors were blinded to the study hypothesis.

Socioeconomic characteristics of the study participants

There were 331 community-dwelling old age people living in the selected cluster kebeles. A total of 293 old age people aged 60 years and above were recruited. Of them, 271 took the allocated intervention, but only 219 (80.81%) finished the intervention and were included in the statistical analysis. The remaining 13 old age people were unable to meet the inclusion criteria; 62 declined to participate in different stages of the intervention; 18 were admitted to the hospitals for various reasons; and seven deaths were reported. The recruitment procedure and flow chart of the study is described in Fig. 1 at the in the Figure legends.

Self-reported participants’ ages ranged from 60 to 98 years old at the baseline and from 60 to 92 years after the intervention. The mean age with standard deviation was 73.1 ± 7.3 before and 72.3 ± 6.8 years after the intervention, respectively. Three-fourths of respondents (75.3% before and 77.6% after) had access to food, whereas one-fourth (24.7% before and 22.4% after) had experienced mild to severe food insecurity in the four weeks before the survey (Table 1).

Table 1: Socioeconomic characteristics of the study participants, Bahir Dar City, 2022

s/no	Variables	Categories	Pretest N (%) (n=271)	Posttest N (%) (n= 219)
	Sex	Female	148(54.6)	132(60.3)
	Sex	Male	123(46.4)	87(39.7)
	Age	60-64	4(1.5)	4(1.8)
		65-69	78(28.8)	74(33.8)
		70-74	91(33.6)	68(31.1)
		75-79	42(15.5)	33(15.1)
		80-84	29(10.7)	23(10.5)
		≥ 85	27(10.0)	17(7.8)
	Religion	Orthodox	190(70.1)	159(72.6)
	Religion	Islam	81(29.9)	60(27.4)
	Marital status	Married	128(47.3)	106(48.4)
		Divorced	47(17.3)	43(19.6)
		Widowed	96(35.4)	70(32.0)
	Educational level	Unable to read and write	144(53.1)	114(52.1)
		Can read and write	84(31.0)	72(32.9)
		Grade 1-8	36(13.3)	30(13.7)
		Grade 9 & above	7(2.6)	3(1.4)
	Current occupation	Housewife	16(5.9)	12(5.5)
		Government employed	10(3.7)	7(3.2)
		Merchant	86(31.7)	74(33.8)
		Daily laborer	2(0.7)	2(0.9)
		No work/retired	157(57.9)	124(56.6)
	Live with	Alone	56(20.7)	51(23.3)
	Live with	With others	215(79.3)	168(76.7)
	Household Wealth index	Poorest	52(19.2)	42(19.2)
		Poor	17(6.3)	14(6.4)
		Middle	92(33.9)	72(32.9)
		Rich	52(19.2)	39(17.8)
		Richest	58(21.4)	52(23.7)
	Food insecurity	Secured access	204(75.3)	170(77.6)
		Mild insecure access	60(22.1)	45(20.6)
		Moderate insecure access	2(0.7)	2(0.9)
		Severely food insecure	5(1.9)	2(0.9)

Nutritional status

The MNA tool revealed that more than half of the study participants were at risk of malnutrition before (55.4%) and after (55.7%) the nutritional counselling intervention. Whereas, 34(12.5%) of them were malnourished before implementing the intervention, compared to 21(9.6%) in the second evaluation after the programme (Fig. 2).

Overall, the mean score of MNA increased from 21.55 ± 3.72 before the implementation of the intervention to 21.64 ± 4.12 immediately after the programme. The mean difference was statistically significant (x̄ = -0.30, t₂₁₈ = -2.72, 95% CI: -0.52- (-0.83), p = 0.007). The mean body weight and BMI, however, did not change after the program's adoption. More than one third (37.3% and 37.9%) of the participants were underweight, while less than a quarter (22.5% and 20.6%) of them were overweight or obese before and after the program's implementation, respectively. The mean body weight was 58.2 ± 7.6 kg before and 57.9 ± 7.5 kg after the intervention.

Nutritional knowledge

In the post-test, every study participant (n = 219) said they had gone over the counselling materials offered. However, 263(97%) of the study participants before the intervention and 204 (93.2%) after the intervention were aware that the quantity of food should change as people age. While only 6(2.2%) and 170 (77.6%) of them were aware that the quality of food should change as people aged before and after the counselling intervention, respectively. Besides, 162(74.0%) knew that old age people should eat more frequently than three times daily. Nevertheless, 35 (16.0%) and 28 (12.8%) of the study participants were still unaware that old age people should consume less fatty and salty food than adults, respectively.

The mean nutrition knowledge scores of the study participants considerably increased from 7.58 ± 1.05 before the implementation of the counselling intervention to 11.61 ± 1.37 immediately after the intervention. There was a significant average difference between pre- and post- test scores (t₂₁₈ = -32.79, p < 0.001). Post-test scores were 3.98 points higher on average than pre-test scores (95% CI: -4.21-(-3.73)). Overall, 125(57.1%) of study participants after the counselling were found to have good knowledge, as opposed to 137(50.6%) before. In contrast, 134 (49.4%) and 94(42.9%) had scored poorly on knowledge tests conducted before and after the training, respectively.

Constructs of the behavioural models

The mean score of all health belief models and theory of planned behavior constructs changed after the intervention. The mean score of the perceived susceptibility, severity, benefits, behavioural beliefs, cues to action, and intentions increased after the nutrition counselling compared to before the intervention. The result of the paired t-test also showed that there was a statistically significant difference (P < 0.05), except for the constructs of perceived severity, behavioural beliefs, and cues to action.

On the other hand, the mean score of perceived barriers, normative beliefs, and perceived self-efficacy decreased after the intervention, yet, the paired t-test result showed a statistically significant difference (P < 0.001) only for the perceived barriers (Table 2).

Table 2

Behavioural Model Constructs of Study Participants, Bahir Dar City, 2022
Behavioural Model Constructs	Pre-test (n1 = 271)		Post-test (n2 = 219)		p-value
Behavioural Model Constructs	Mean	SD	Mean	SD	p-value
Perceived susceptibility	8.61	1.40	8.69	1.64	< 0.001^*
Perceived severity	15.07	1.43	15.13	1.50	0.318
Perceived Benefits	19.04	1.86	19.78	1.80	< 0.001^*
Perceived Barriers	34.14	1.50	33.99	1.59	< 0.001^*
Behavioral beliefs	36.00	0.06	36.01	0.10	0.083
Normative Beliefs	10.63	0.93	10.60	0.92	0.318
Perceived Self efficacy	8.64	1.98	8.53	1.98	0.18
Cues to action	7.62	0.30	8.83	0.34	0.14
Intentions	16.01	0.09	16.04	0.20	0.035^*
^*P-value is significant (P < 0.05) according to paired sample t-test

Dietary practice

The majority of the respondents, 180(66.4%) and 152(69.4%) had regular meal practices before and after the intervention, respectively. About 65.3% had three meals per day both before and after the intervention, while 92(33.9%) and 71(32.4%) of them had two meals per day before and after the intervention, respectively. However, none and only five (2.3%) of the respondents took the recommended five meals every day, respectively, before and after the intervention.

The study participants consumed nearly identical dietary varieties before and after the intervention. Starchy staples, legumes, and spices were the most commonly consumed food groups, whereas animal products, fruits, and vegetables were rarely consumed before and after the intervention. Still, the study participants increased their consumption of dairy products (x̄ = -0.10, t₂₁₈ = -4.19, 95% CI: -0.14-(-0.05), p < 0.001), meat/fish/egg (x̄ = -0.13, t₂₁₈ = -5.77, 95% CI: -0.09-(-0.18), p < 0.001), and fruit (x̄ = -0.13, t₂₁₈ = -5.77, 95% CI: -0.09-(-0.18), p < 0.001) after the counselling intervention. However, their changes in vegetable intake were not statistically significant (x̄ = -0.01, t₂₁₈ = -1.0, 95% CI: -0.01-(-0.03), p = 0.32) (Fig. 3).

The dietary diversity score (DDS) increased from 5.00 ± 0.34 before the intervention to 5.37 ± 0.70 after the intervention, and the change was statistically significant (x̄ = -0.38, t₂₁₈ = -7.17, 95% CI: -0.48-(-0.27), p < 0.001). Similarly, the proportion of participants having adequate DDS (having four or more DDS) increased from 254(93.73%) before to 209(95.43%) after the intervention.

This study was conducted to investigate the effect of behavioural model-guided nutritional counselling on the nutritional status of the community-dwelling old age population in Bahir Dar City, Northwestern Ethiopia.

Only 32.1% and 34.7% of study participants had normal nutritional status based on MNA before and after the intervention, respectively. The results are less than those of the studies in Egypt (33) and Lithuania (18), where 46% and 51.5% versus 88% and 53.7% of the studied population had normal nutrition before and after the intervention, respectively. While the nutritional status measured by BMI revealed that 40.2% and 41.6% of old age people in this study had normal weight before and after the intervention, respectively. This is more than the findings from Egypt, where 29% of participants had normal weight prior to the intervention and 34% after three months (33).

The socioeconomic disparities and differences in health literacy among the study population could be one explanation for this variance.

On the other hand, the mean body weight and the BMI in this study did not change significantly, while the mean score of MNA significantly increased after the programme. This is consistent with earlier research from Vietnam (34), Netherlands (35), Norway (36), and Finland (37), which found an increase in MNA scores but no appreciable change in body weights or BMI. This discrepancy may be due to the nature of the MNA tool, which measures many factors and is more sensitive to change than just body weight or BMI.

The overall nutritional knowledge level also increased from pre-intervention to post-intervention, consistent with earlier studies (8, 33, 38, 39). Additionally, the mean score of the perceived susceptibility, benefits, and intentions significantly increased after the nutrition counselling compared to before the intervention. On the other hand, the mean score of perceived barriers significantly decreased after the intervention. These results are in line with the study from Iran, which found that older women's perceptions, beliefs, and behaviors around nutrition were significantly improved after HBM-based nutritional counselling (8).

Moreover, the majority of study participants had regular breakfast, lunch, and dinner practices before and after the intervention. In a similar fashion, two-thirds of older adults in the United States consumed three meals on a day of intake (40). However, lunch was the most often skipped meal in the United States (40), in contrast to the current study, where breakfast was the meal that most study participants frequently skipped. The discrepancies might be due to cultural and health literacy differences.

Although only 2.3% of the study participants in the current study took the recommended five meals every day after the intervention, they reported changes in the number of meals and snacks they consumed per day after nutritional counselling. The results are consistent with the studies from Europe (17), Finland (37), and Vietnam (34), where study groups reported a positive change in dietary intake across all nations after receiving individualized nutritional guidance, despite the fact that participants in the various study locations had differing baseline dietary intakes.

The present study also discovered a positive effect of the implementation of the nutritional counselling program on the self-reported consumption of the majority of food categories, such as dairy products, fruits, and meat or egg intake. However, no changes were observed in the starchy staples, legumes, fats, or sweet foods. Similar findings from Egypt (38, 39) revealed statistically significant increases in the intake of dairy products, vegetables, and fruits, while statistically significant decreases in the frequency of cereal and fluid intakes were observed before and after the study intervention, but no significant changes in protein intake. Whereas, study participants in Finland reported increasing their intake of protein-rich foods after receiving individualized dietary counselling (37). Moreover, interventional studies revealed that eating more frequent and smaller meals with protein-rich breakfast and lunch improved diet quality, lowered BMI, and preserved lean tissue mass in older adults (41, 42).

Overall, the majority of the study participants had adequate DDS and the change is also statistically significant. Yet, there was a low intake of animal products and fruits, while there was a high consumption of oils, fats, sweets, spices, coffee, and alcoholic beverages. This is comparable to the poor dietary habits of Ethiopians (43) and other African populations (39), which have a low intake of animal-source foods, vegetables, and fruits and a high intake of cereals, salt, and a rising trend in the consumption of saturated fat and oil.

Strengths and limitations of the study

To our knowledge, this is the first study that estimates the effects of behavioural model-guided nutritional counselling on community-dwelling old age people’s nutritional status. This study has strengths, as the data collection and the counselling intervention were conducted by separate people, which could have decreased some bias.

However, the following are some limitations of the current study: First, the reliability of self-reported data and a single 24-hour dietary intake recall in the study population must be considered, as well as other factors including low educational levels and the decline of sensory abilities with ageing. Second, since this is a pre-post quasi-experimental design, the study's ability to draw a causal relationship between the intervention and outcomes is limited.

Behavioral model-guided nutritional counselling improves the nutritional status of old age people. The study participants' perception of risks, on the other hand, increased with the intervention. A participant-centered nutritional programme recommended to improve the health of community-dwelling older people. Therefore, health practitioners should train those who interact with or assist the elderly. Policymakers should integrate initiatives to educate old age people about their diet and nutritional status within the federal nutrition services programmes already in existence. Furthermore, further research should examine the effect of more intensive counselling considering the limitations of this study.

QoL

quality of life

WHOQOL-OLD

world health organization quality of life-for older adults

MNA

mini nutritional assessment

BMI

body mass index

Ethical approval and formal consent

This study was carried out in accordance with the Declaration of Helsinki's rules (44). Additionally, each study participant gave verbal informed consent, and this as well as all the research protocols were first approved by the Institutional Ethical Review Board (IERB) of Bahir Dar University, College of Medicine and Health Sciences, IEB meeting No. 001/2021, Protocol No. 002/2021, Date January 6, 2021, and Assigned No. 003. Furthermore, official letters of cooperation obtained from the IEB were given to the Bahir Dar City Administrative Health Department and then to the respective offices of the selected study sub-cities and Kebeles, the smallest administrative unit in Ethiopia.

Consent for publication

Not applicable

Availability of data and materials

All data generated or analyzed during this study are included in this published article and its tables, and figures.

Competing interests

The authors have declared that they have no competing interests.

Funding

The research was supported by Bahir Dar University. The University had no involvement in the study's design, data analysis, result interpretation, article writing, or publication decision.

Author contributions

AM planned the research, analyzed the data, and wrote the paper. NF was involved in the design, data analysis, manuscript preparation, and critical evaluation of the study. Both authors read and approved the final manuscript.

Acknowledgements

We would like to thank Bahir Dar University for allowing us to perform this research. Our sincere thanks go to all of our study participants and counsellors who participated in the research.

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No competing interests reported.

Effect of Behavioural Model-Guided Nutritional Counselling on Old Age People’s Nutritional Status: A Quasi-Experimental Study Design

Status:

Journal Publication

Version 1

Abstract

Figures

Background

Methods

Study design and period

Study population

Sample size and sampling procedure

Intervention approach

Intervention fidelity

Data collection instruments and procedures

Data processing and analysis

Data quality management

Results

Socioeconomic characteristics of the study participants

Nutritional status

Nutritional knowledge

Constructs of the behavioural models

Dietary practice

Discussion

Strengths and limitations of the study

Conclusion

Abbreviations

Declarations

Ethical approval and formal consent

Consent for publication

Availability of data and materials

Competing interests

Funding

Author contributions

Acknowledgements

References

Additional Declarations

Status:

Journal Publication

Version 1