Research Article

Effect of Different Dietary Levels of Protein on the Proximate Composition of Genetically Improved Farmed Tilapia (GIFT) from Pakistan

Anila Kousar, Muhammad Naeem* and Samrah Masud

Institute of Pure and Applied Biology, Zoology Division, Bahauddin Zakariya University, Multan, 60800, Pakistan.

Received | December 21, 2018; Accepted | March 08, 2020; Published | April 25, 2020

*Correspondence | Muhammad Naeem, Institute of Pure and Applied Biology, Zoology Division, Bahauddin Zakariya University, Multan, 60800, Pakistan; Email: [email protected]

Citation | Kousar, A., M. Naeem and S. Masud. 2020. Effect of different dietary levels of protein on the proximate composition of genetically improved farmed tilapia (GIFT) from Pakistan. Sarhad Journal of Agriculture, 36(2): 517-525.

DOI | http://dx.doi.org/10.17582/journal.sja/2020/36.2.517.525

Keywords | Proximate composition, Condition factor, Graded levels of crude protein, Genetically improved farmed tilapia (GIFT), Hapas, Body size

Introduction

It is important for any food to contain quality nutrients (Nettleton, 1992). According to James (1998) fish is consumed by a large number of people in the whole world and provides quality nutrients to their consumers. The quality of food depends on the quantities of nutrients present in it and their bioavailability. Man is interested in healthy food because health is dependent on quality diet (Lie, 2001). Fish is a good source of protein and fish fat is important because it contains n-3 fatty acids (Bennett et al., 2018). It is important to study the status of nutrients present in fish due to high demand of fish and its products (Adefemi, 2011). The quality of nutrients present in food describes its proximate composition. It is necessary to assess the nutritional value and quality of fish being eaten (Azam et al., 2004).

There is an increasing interest in the studies of body composition of fish because safety and quality of fish and its products are in great demand (Dumas et al., 2010). The body composition represents an important feature of nutrients quality. It can be assessed through the analysis of protein, fat and ash present in the food making it valuable (Shehawy et al., 2016).

Fish is consumed by large human population globally due to presence of high quality protein, its availability, palatability and deliciousness (Foran et al., 2005). So, it is necessary to check the proximate composition of fish before its consumption (Fawole et al., 2007) as it promotes growth (Ugwu et al., 2007). Bano et al. (2019) documented that increasing level of protein in diet enhances the whole body contents of protein.

Nile tilapia (Oreochromis niloticus) is a popular fish (Jim et al., 2017) and shows variations in protein requirement with the size/age, protein quality, water temperature, salinity, non-protein energy levels, presence of natural food and allowance of feed (NRC, 1993). A selective breeding program was carried out to improve the Nile tilapia. A base population of Nile tilapia was selected for several generations to develop the GIFT strain (Eknath and Acosta, 1998). The GIFT strain was developed from 20 years of selection (Bentsen et al., 1998).

Available data on proximate analysis of GIFT is scarce (De-Silva et al., 2016). So, the present study aimed to investigate the impact of different protein diets on proximate composition of GIFT.

Materials and Methods

Three diets consisting of 15 %, 20% and 25% crude protein were prepared using the cheap plant ingredients. Plant origin feed ingredients used to formulate experimental feed included soyabean meal, sunflower meal, canola meal, rice polish, mustard meal, wheat bran, corn gluten and limited quantities of fish meal. These ingredients were purchased from the local market and were grinded finely for its easy ingestion by fish.

Five days old GIFT fingerlings of were collected, acclimatized for two weeks, and transferred to hapas (8×6×3 ft) at random. Fingerlings were fed fish meal @ 10 % during acclimatization period and experimental feed at the rate of 5% up to the end of experiment. The experiment was carried out in duplicate for ninety days. All the specimens were collected on the completion of feeding trial from the fish farm (Tawakkal Tilapia Hatchery) where experiment was carried out. It is located at Tawakkal Nagar Muzaffar Garh, Punjab, Pakistan. Ten fishes were randomly selected from each treatment hapa for the estimation of biochemical constituents of studied GIFT. These samples were washed, dried and MS222 was used for anaesthetizing them. For the measurement of wet weight and total length of samples digital electric balance (Shimadzu ELB – 300 Japan) and measuring wooden tray were used respectively.

All the dead and pre- weighed samples were placed individually in an aluminum foil tray. These trays were kept in an electric oven at 70ºC till constant weight of samples was obtained. Percent dry weight and water contents in fish were measured as given below.

% dry weight = (dry weight / wet weight) × 100

All the samples were then grinded using pestle and mortar to a fine powder for analyzing other body components.

Fat content in samples were measured with the help of dry extraction method (Bligh and Dyer, 1959). In this method, chloroform and methanol were mixed together in a ratio of 1:2. One gram of fish powder was taken in a clean glass test tube and 10 ml of this mixture was poured in it. Test tubes were stirred well and left for one night. Clean small glass tubes were used for taking the clear supernatant from the test tubes. In the incubator (Memmert ® 8540) all bottles were kept for evaporation of samples at 50ºC to obtain fat. The obtained contents of fat were measured using electric balance Shimadzu ELB-300 Japan. The amount of fat was then obtained by the subtraction of weight of empty glass bottles from the fat containing bottles. Percent fat in all the samples was calculated as given below.

Percent fat in the wet weight of fish = (total fat present in fish / wet weight of the fish body) × 100

Percent fat present in dry weight = (total amount of fat in fish / dry weight of fish) × 100

The amount of ash in samples was measured by taking one gram powder fish in china crucible which were pre weighed. These crucibles were then kept in muffle furnace for 24 hours at a temperature of 500ºC. After removing from furnace weight of crucibles was taken again on cooling. Weight of ash was obtained on subtracting the content of ash from the weight of initial sample. Same method was used for getting percent ash in dry and wet weights of fish.

The mass of ash and fat was subtracted from the dry weight of fish to get total amount of protein by following Caulton and Bursell (1977) and Salam and Davies (1994). Amount of percent protein in wet and dry fish weight was obtained similar to % ash and % fat.

The condition factor was measured by dividing the weight of fish with the cube of length of fish and then multiplying with 100 following Wooton (1990) and Salam and Davies (1994).

Analysis of data

Means, ranges, standard deviations and errors were calculated. MS-Excel program was used to apply regression, correlation coefficients and student’s t- test following Zar (1996) and Naeem and Ishtiaq (2011).

Results and Discussion

Effect of three different protein diets (T1=15% CP, T=20% CP and T3=25% CP) in GIFT was evaluated for proximate composition. Table 1 summarizes means of percent water, ash, fat, protein and organic content in the dry and wet weights of fish for T1, T2 and T3 are summarized in Table 1.

Water content in GIFT were found highest in treatment 2 (T2), in which fish were fed with 20% dietary protein, followed by treatment 1 (T1, 15% dietary protein) and treatment 3 (T3, 25% dietary protein). Protein and organic contents were highest while fat was lowest in T3 fish on dry weight basis. Ash content was higher in T2 fed fish than T1 and T3 (Table 1).

Most of the % body constituents yielded non-significant correlation (P > 0.05) with % water except for %fat dry weight (T2, P<0.01), % protein wet weight (T3, P<0.001) and % organic content wet weight (T1and T3, P<0.001) and (T2, P<0.05) (Table 2).

The regression analysis yielded positive and strong correlation (P<0.001) for log transformed data of total water with wet body weight (Table 3) and total length (Table 4) for all the treatments, while, correlation of total fat was found non-significant (P>0.05) for all treatments. Log transformed data of total protein and total ash indicated positive and significant correlations with body weight and total length in GIFT fed 15% and 25% CP but relationship was found non-significant (P>0.05) for 20% CP fed fish. Organic content yielded significant positive correlation for all the three treatments. The value of slope (b<3) exhibited negative allometry in all the parameters of proximate composition for T1, T2 and T3 with total length (Table 4). Negative allometry (b<1) was found in log water (T1, T3) but positive allometry (b>1) for T2 with log values of wet weight. Positive allometry existed for log values of protein, ash, and organic content (T1, T3) but negative allometric growth was observed for T2 fed fish against log wet body weight (Table 4).

The values of mean condition factor for GIFT were 1.50±0.19 with range 1.30-1.97 for T1 (15% CP), 1.43±0.14 with range 1.22-1.63 for T2 (20% CP) and 1.29±0.28 with range 0.75-1.73 for T3 (25%) diets. It did not show any effect on percent body components like protein, water, ash and organic content (T1, T2 and T3), %fat (T1 and T3) except for %fat (T2) which showed least positive correlation (P>0.05) (Table 5).

The proximate composition helps in the assessment of physiological and feeding conditions of the fish (Chandrashaker et al., 2004). The results obtained on water, ash, fat, protein and organic content, expressed in grams, in the present work exhibited approximately similar values as reported by other investigators for same and other fish species (Table 1). The values of water, fat and ash content are best supported by findings of Bandarra et al. (2009), in scabbardfish, water content in Tilapia mossambis (Adefemi, 2011) ash and fat content in Nile tilapia (Jim et al., 2017), fat and protein in GIFT (De Silva et al., 2016). Our findings of protein content both wet and dry weight basis are higher than those reported by Khalid and Naeem (2018) in Ctenopharyngodon idella. These variations may be the result of different environmental conditions and diet composition (Ebrahimi and Ouraji, 2012).

The proximate analyses result of this study indicated that major component of fish body was water. The water content recorded as 79.13%, 80.85% and 78.48% for T1, T2 and T3 respectively, are similar to the findings of Adefemi (2011) 79.50% in Tilapia mossambis and Naeem et al. (2011a) in hybrid Catla catla × Labeo rohita (79.13%), 80.80% for cultured Oreochromis niloticus by Job et al. (2015) and 80.76% for Ctenopharyngodon idella by Khalid and Naeem (2018). But our present findings deviate from the results of Osibona et al. (2009) in Clarias garipinus 74.3% and Yousaf et al. (2011) in Wallago attu 76.19%. These differences may be due to variations in many factors like environment, type of feed and maturity stage of fish (De Lange et al., 2003).

Table 1: Values of means and ranges of different body components of GIFT (n = 10).

Body components	Diet variables	Means ± standard deviation	Ranges
Water contents (%)	T1 T2 T3	79.13±1.44 80.85±1.12 78.48 ±2.40	76.92-81.45 78.63-82.79 75.14-84.09
Ash content (%Wet weight)	T1 T2 T3	2.75±0.71 3.27±0.47 3.30±0.07	1.34-3.75 2.66-4.09 1.65-4.37
Ash content (%dry weight)	T1 T2 T3	13.13±3.13 16.19±1.55 15.47±3.50	1.34-3.75 14.09-18.15 7.93-20.00
Fat content (%wet weight)	T1 T2 T3	3.74±1.65 2.62±0.69 2.82±1.18	2.03-6.92 1.87-3.67 1.59-4.97
Fat content (% dry weight)	T1 T2 T3	18.00±7.89 13.37±4.19 13.00±4.83	10.00-30.00 10.00-20.00 10.00-20.00
Protein contents (%wet weight)	T1 T2 T3	14.43±2.00 14.00±1.73 15.39±1.99	10.24-16.97 10.74-16.36 11.44-19.10
Protein contents (%dry weight)	T1 T2 T3	69.07±8.15 70.23±4.35 71.53±3.84	55.22-77.00 62.38-75.00 65.00-77.89
Organic content (% wet weight)	T1 T2 T3	18.12±1.21 16.62±1.41 18.22±2.44	15.81-19.83 14.18-18.64 13.03-21.55
Organic content (% dry weight)	T1 T2 T3	82.06±17.09 83.60±1.49 84.53±3.50	82.06-93.04 81.85-85.91 80.00-92.07

 

The results of the present study represented lowest water contents and highest protein content in GIFT fed with 25% dietary protein. These findings coincide with those reported by Bano et al. (2019) in Labeo calbasu and Ishtiaq and Naeem (2019) in Catla catla who had studied the effect of dietary protein levels on body composition. They found highest protein and lowest water content in fish samples fed upon 25% CP. In Labeo rohita fingerlings, increase in lipid and protein with decrease in water content had been reported with dietary protein levels (Satpathy et al., 2003).

The relationship between percent water and proximate components (fat, ash, protein and organic content) is used as predictors of fish body composition. In the present study, equations were developed between percent water and percent of each of proximate constituents which showed non-significant relation (P>0.05) except for percent fat dry weight (T2,), % organic wet weight (T1, T2, T3) and % protein wet weight (T3). The results of relationships of % water and each percent composition parameters are best supported by Naeem et al. (2011a) in hybrid Catla catla × Labeo rohita and Bano et al. (2019) in L. calbasu.

Previously many studies indicated inverse relationship between percent water, percent fat and percent protein in fish whole body (Yousaf et al., 2011; Naeem et al., 2011b). The present work examined that relation of water and fat wet weight was not significant as shown by predictive equations. Although fat dry weight was found significant in T2 fed GIFT while non-significant inverse relationship was observed between percent water and percent fat in T1 and T3 (wet weight) and T3 (fat dry weight). Naeem et al. (2013) and Khalid and Naeem (2018) have reported the same trend.

Percent water showed strong inverse correlation with percent protein wet weight in T3 and strongly inverse correlation with organic content in T1 and T3 while direct least significant in T2 diet fed GIFT. Similar results have been documented by Naeem et al. (2011a) in hybrid (Catla catla × labeo rohita). Naeem and Ishtiaq (2011) also documented strong inverse correlation between percent water and organic content. The present findings declared non-significant relationships of % water and ash (wet and dry weight) in T1, T2 and T3. Naeem et al. (2011a) reported similar non-significant relation in hybrid Catla catla × Labeo rohita.

Predictive equations were made to observe the influence of body size on the total body constituents of studied GIFT. The results showed definite influence of wet weight and total length on various body constituents of GIFT fed upon different dietary protein. The relationship between log transformed data of wet body weight as well as total length versus

Table 2: Relation between percent water and percent components of GIFT body (n=10).

Relations	Diet variables	Correlation coefficients (r)	intercept (a)	slope (b)	Standard error of (b)	t value when b=0	p-value
% Water (x) %Fat wet weight (y)	T1 T2 T3	0.010ns 0.286ns 0.472ns	4.65 -11.74 20.35	-0.0116 0.1777 -0.2233	0.403 0.211 0.147	-0.029 0.844 -1.515	0.978 ns 0.423 ns 0.168 ns
% Water (x) %Fat dry weight (y)	T1 T2 T3	0.193ns 0.787** 0.247ns	-65.55 8.24 50.47	1.056 2.4967 -0.4775	1.894 0.692 0.661	0.557 3.609 -0.722	0.592ns 0.007** 0.491ns
% Water (x) %Protein wet weight (y)	T1 T2 T3	0.521ns 0.624ns 0.893***	71.52 6.46 71.17	-0.7215 2.3048 -0.7108	0.417 1.021 0.126	-1.729 2.257 -5.624	0.122ns 0.054 ns 0.000***
% Water (x) %Protein dry weight(y)	T1 T2 T3	0.071ns 0.101ns 0.019ns	100.86 67.16 69.21	-0.4018 0.9377 0.0296	1.991 3.258 0.542	-0.202 0.288 0.055	0.845ns 0.781ns 0.957ns
%Water (x) %Ash wet weight (y)	T1 T2 T3	0.541ns 0.204ns 0.226ns	23.79 3.61 8.48	-0.6498 -0.3011 -0.0659	0.730 0.511 0.100	-0.889 -0.589 -0.657	0.106ns 0.572ns 0.529ns
% Water (x) %Ash dry weight (y)	T1 T2 T3	0.300ns 0.134ns 0.320ns	64.55 30.89 -19.68	-0.6498 -0.1792 0.4479	0.729 0.468 0.469	-0.891 -0.383 0.956	0.399ns 0.711ns 0.367 ns
% Water (x) % Organic contents wet weight (y)	T1 T2 T3	0.874*** 0.668* 0.957***	76.20 10.07 91.52	-0.7340 2.0037 -0.9340	0.144 0.789 0.100	-5.083 2.54 -9.309	0.000*** 0.035* 0.000***
% Water (x) % Organic contents dry weight (y)	T1 T2 T3	0.308ns 0.134ns 0.320ns	35.46 69.11 119.68	0.6498 0.1792 -0.4479	0.730 0.468 0.469	0.889 0.383 -0.956	0.399 ns 0.712 ns 0.367 ns

***P<0.001; **P<0.01; *P< 0.05; nsP>0.05

Table 3: Relation between log wet weight (g) and total log components of GIFT body (n = 10).

Relations	Diet Variables	Correlation coefficients (r)	intercept (a)	Slope (b)	Standard error of (b)	Value of t when b = 1	P-value
log body weight (x) log water content (y)	T1 T2 T3	0.997*** 0.987*** 0.980***	-0.08 -0.16 0.02	0.9771 1.0639 0.8968	0.029 0.061 0.064	33.854 17.363 14.088	0.000*** 0.000*** 0.000***
log body weight, g (x) log fat content (y)	T1 T2 T3	0.387ns 0.088ns 0.415ns	-1.31 -0.35 -1.76	0.8628 -0.1633 1.1537	0.727 0.657 0.894	1.187 -0.248 1.290	0.629ns 0.081ns 0.233ns
log body weight (x) log protein content (y)	T1 T2 T3	0.833** 0.591ns 0.874**	-0.99 -0.631 -1.29	1.1190 0.7885 1.4056	0.263 0.381 0.276	4.259 2.071 0.708	0.002** 0.072 ns 0.000***
log body weight (x) log ash content (y)	T1 T2 T3	0.709* 0.584ns 0.708*	-1.97 -1.34 -2.23	1.3354 0.8621 1.6284	0.470 0.424 0.574	2.841 2.034 0.574	0.021* 0.076 ns 0.021*
log body weight (x) log organic contents (y)	T1 T2 T3	0.962*** 0.717* 0.844**	-0.82 -0.41 -1.17	1.0693 0.6524 1.3636	0.107 0.224 0.306	10.023 2.909 4.449	0.000*** 0.019* 0.002**

P>0.05 = ns; ***P<0.001; **P<0.01; *P<0.05

total water content (Tables 3 and 4) exhibited strong correlation (P<0.001) for T1, T2 and T3. These findings are supported by Naeem and Salam (2010) in bighead carp, Naeem et al. (2011a) in Catla catla × Labeo rohita hybrid, Naeem and Ishtiaq (2011) in Mystus bleekeri, Naeem et al. (2016) in rainbow trout, Khalid and Naeem (2018) in Ctenopharyngodon idella and Bano et al. (2019) in L. calbasu reported similar results.

Log transformed data showed non-significant correlation

Table 4: Relation between log total length (cm) and log total components of GIFT body (n = 10).

Relations	Diet variables	Correlation coefficients (r)	intercept (a)	Slope (b)	Standard error of b	t value when b = 3	p-value
log total length (x) log water content (y)	T1 T2 T3	0.936*** 0.943*** 0.965***	-1.12 -0.7184 0.00354	2.1711 1.7417 1.0427	0.288 0.2169 0.099	7.54 8.0277 10.531	0.000*** 0.000*** 0.000***
log total length (x) log fat content (y)	T1 T2 T3	0.216ns 0.247ns 0.265ns	-1.45 0.24 -1.29	1.1406 -0.7896 0.8699	0.288 1.095 1.119	7.544 1.095 0.778	0.548ns 0.491ns 0.459ns
log total length (x) log protein content (y)	T1 T2 T3	0.745* 0.671* 0.808*	-2.05 -1.28 -1.21	2.3674 1.5335 1.5342	0.749 0.599 0.395	3.161 2.558 3.884	0.013* 0.030* 0.004**
log total length (x) log ash content (y)	T1 T2 T3	0.605ns 0.657* 0.679*	-3.10 -2.03 -2.20	2.6944 1.6617 1.8425	1.255 0.675 0.705	2.147 2.463 2.613	0.064 ns 0.030* 0.039*
log total length (x) log organic contents (y)	T1 T2 T3	0.815** 0.755* 0.744*	-1.72 -0.86 -1.02	2.1410 1.1777 1.4190	0.538 0.361 0.451	3.976 3.262 3.149	0.004** 0.011* 0.014*

*** P < 0.001; **P < 0.01; *P < 0.05, P > 0.05 = ns.

Table 5: Relation between condition factor and percent components of GIFT body (n = 10).

Relations	Diet variables	Correlation coefficients (r)	intercept (a)	Slope (b)	Standard error of b	Value of t when b = 0	p-value
condition factor (x) % water (y)	T1 T2 T3	0.509ns 0.102ns 0.304ns	85.06 82.04 75.01	-3.9706 -0.8309 2.6806	2.369 2.875 2.974	-1.676 -0.289 0.901	0.132ns 0.779ns 0.394ns
Condition factor (x) % Fat (y)	T1 T2 T3	0.538ns 0.728* 0.201ns	-3.41 -2.68 1.74	4.779 3.6995 0.8390	2.649 1.231 1.446	1.804 3.005 0.580	0.109ns 0.017* 0.578ns
Condition factor (x) % Protein (y)	T1 T2 T3	0.123ns 0.100ns 0.364ns	16.41 15.83 18.69	-1.3282 -1.2745 -2.5559	3.781 4.469 2.313	-0.351 -0.285 -1.105	0.734ns 0.783ns 0.301ns
Condition factor (x) % Ash (y)	T1 T2 T3	0.058ns 0.148ns 0.375ns	2.42 3.99 4.55	0.2216 -0.509 -0.9637	1.351 1.202 0.843	0.164 -0.684 -1.143	0.874ns 0.683ns 0.286ns
Condition factor (x) %Organic contents (y)	T1 T2 T3	0.569ns 0.235ns 0.199ns	12.55 13.14 20.44	3.7255 2.4249 -1.7169	1.902 3.545 2.986	1.959 0.684 -0.575	0.086ns 0.153ns 0.581ns

P>0.05 = ns; *P<0.05

(P>0.05) with total fat content versus body weight and total length for T1, T2 and T3 which is contrary to Naeem and Ishtiaq (2011), Naeem et al. (2011a) and Naeem and Salam, 2010. Khalid and Naeem (2018) also documented strong correlation between log values of total length and body weight with all the body constituents in Ctenopharyngodon Idella. The reasons of such variations may be the result of differences in the geography, age, season and sampling type (Abbasi et al., 2017), variations in nutrition as well as size of fish body (Ebrahimi and Quraji, 2012).

The values of slope ‘b’ shows isometric state when b=1 on log transformed relationships. The value of b > 1 in log water (T2), log fat (T3), log protein, log ash and log organic content (T1, T3) indicated positive allometry i.e. these body constituents increased with increasing body weight. Although, negative allometry was observed in log water (T1, T3), log fat (T1, T2), log protein, log ash and log organic content (T2). The negative allometry in log water is supported by findings of Naeem and Ishtiaq (2011), Naeem et al. (2011a, b, c), Naeem et al. (2016), Naeem et al. (2011a, c) and Naeem and Ishtiaq (2011) for log ash content and Naeem et al. (2011a, b) for log fat. Naeem and Ishtiaq (2011) reported positive allometry for log fat, log protein and log organic content which support our findings in log fat (T3), log protein, ash and organic content (T1, T3). Positive allometry in log fat is also supported by Naeem et al. (2016) in rainbow trout. Negative allometry in water (T1, T3) and fat (T1, T2) coincides with findings of Naeem et al. (2011 a, b), while log water (T1, T3) and log ash (T2) are supported by Naeem et al. (2011c), Naeem and Ishtiaq (2011) and Naeem et al. (2016). Although, all the body components exhibited negative allometry (b<3) with total length showing deviation from cube law.

Most of the regression relationships between condition factor and various body constituents showed non-significant correlation except for % fat suggesting no influence of condition factor on these constituents. Khalid and Naeem (2018) has also documented non-significant correlation between condition factor and % fat, %protein, %ash while least significant correlation with water and organic content. Naeem et al. (2011b), Naeem and Ishtiaq (2011) and Naeem et al. (2017) have also reported similar non-significant findings in all the body constituents of female farmed Oreochromis mossambicus and Mystus bleekeri and Cirrhinus mrigala, respectively.

Conclusions and Recommendations

The present study concludes that different levels of dietary proteins and body size have definite influence on the proximate composition. It also assists to model growth of fish and protein deposition rate at graded dietary protein levels. The findings of the investigation confirmed that proximate composition parameters show variation with different protein diets. The obtained results reveal that GIFT possesses more amount of protein and low fat contents fed upon 25% CP diet. It will contribute to the nutritional qualities and growth of human beings as indicated by high protein content and is best for human consumption.

Novelty Statement

Results of this study shows that highest protein contents of Genetically Improved Farmed Tilapia (GIFT) can be achieved by feeding a diet containing 25% crude protein.

Author’s Contribution

Anila Kousar conducted the experiment and lab work, collected and analyzed data and wrote the manuscript. Muhammad Naeem supervised the research work, made available the necessary circumstances for the completion of experiment and assisted in the manuscript writing. Samrah Masud helped in data analysis.

Conflict of interest

The authors declare that they have no conflict of interest.

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