Original Article
Nutritional Status of Mother and Gestational Age
Authors:
Avinash H. Salunkhe, Krishna Institute of Nursing Sciences, KIMSDU, Karad, Maharashtra, India,
Asha Pratinidhi, Dept. of Community Medicine, KIMS, KIMSDU, Karad, Maharashtra, India,
SV Kakade, Dept. of Community Medicine, KIMS, KIMSDU, Karad, Maharashtra, India,
Jyoti A. Salunkhe, Krishna Institute of Nursing Sciences, KIMSDU, Karad, Maharashtra, India,
Vaishali R. Mohite, Krishna Institute of Nursing Sciences, KIMSDU, Karad, Maharashtra, India,
Trupti Bhosale, Krishna Institute of Medical Sciences Deemed University Karad, Maharashtra, India.
Address for Correspondence
Avinash. H. Salunkhe
Krishna Institute of Nursing Sciences,
Krishna Institute of Medical Sciences Deemed University Karad
Karad, Satara District, Maharashtra, India.
E-mail: salunkheah@gmail.com.
Citation
Salunkhe AH, Pratinidhi A, Kakade SV, Salunkhe JA, Mohte VR, Bhosale T. Nutritional Status of Mother and Gestational Age. Online J Health Allied Scs. 2017;16(4):2. Available at URL:
https://www.ojhas.org/issue64/2017-4-2.html
Submitted: Sep 26,
2017; Revised: Nov 4, 2017; Accepted: Jan 2, 2018; Published: Jan 30, 2018. |
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Introduction:
Pregnant women form one of the most vulnerable segments of the population from nutritional point of view. Numerous studies in India and elsewhere have shown that in chronically undernourished women subsisting on unchanged dietary intake in pregnancy and lactation have an adverse effect on maternal nutritional status. ICMR district nutrition survey 1999-2000 reported prevalence of anemia as 84.2% with 13.1% with severe anemia in pregnancy.[1]
Epidemiological studies from India documented the magnitude and adverse consequences of chronic energy deficiency (CED) on the mother and child and paved way for effective intervention programs to address under nutrition during pregnancy and lactation. Over 75% of pregnant women in India are anemic and anemia remains to be a major factor responsible for maternal morbidity and mortality.[2,3] Nutritional problems may be caused not only by deficiency of protein, calorie, iron, Vitamin C etc, but by other conditions like malaria, worm infestation, adverse environmental and socio-demographic factors. Association of nutritional problem with adverse maternal outcome such as puerperal sepsis, anti partum hemorrhage, post partum hemorrhage etc., are also responsible for low birth weight, premature birth, high perinatal mortality rate and decreased work capacity.[3]
Material and Methods:
A comparative, exploratory approach and Prospective Cohort study design was used to identify maternal risk factors influencing on gestational age. All consecutive sub set of 380 eligible mothers delivered at Krishna Hospital, Karad till the desired sample size was reached were included in the study. The data was collected by using structured interview schedule. Assessment of mother was done by taking selected anthropometric measurement like height in cm, dietary history of 24 hours recall method and laboratory parameters of hemoglobin. The data were collected after formal permission from hospital authorities and after taking informed consent from each respondent. The data was collected for two years from the ANC mothers who were registered at antenatal clinic of Krishna Hospital, Karad. Out of 380 pregnant women i.e. study population LMP was not known for 15 women were excluded from 380 cases and remaining 365 were considered for final analysis.
24 hour’s diet recall: Each woman was asked about her dietary intake by recall method. The mother recalled what and how much food was consumed and when it was consumed. The mothers were asked to express the consumption of all food items in terms of exact Katori/ wati/ glass size, Chapati or Bhakari size and number, spoon size (large, medium, small). This information was used to compute the daily intake of foods by converting the household measures into grams or kilograms. The daily intake of calories (Kcal); proteins (g); calcium (mg); iron (mg) was calculated and compared with Recommended Dietary Allowance (RDA) of energy/ Calorie requirement during pregnancy on individualized babies as per ICMR guidelines.[4] The recommendations take into consideration body weight, type of work and sex. The individualized caloric requirement was obtained from the Table that has values for every five kilogram weight from 40 kilogram to 70 kilogram for women.[4] The individualized protein requirement was found out using the formula of 1.04/kg of weight [5-8] at the time of registration as a proxy for pre-pregnancy weight. Calcium and iron requirements were taken from the general recommendations given by ICMR.[5-8] To these pre-pregnancy requirements of nutrients, RDA for pregnancy of calories, proteins, calcium and iron were added to get individualized requirements of these nutrients during pregnancy.
Mothers’ data:
The researcher trained the birth attendants in maternity ward and supervised the data collection procedure. Ten percent measurements were taken by the researcher and validated the data abstracted from the mothers’ records, such as infant birth weight, type of delivery etc.
The nursing staff conducting delivery or being present at the time of delivery were
pre-trained in recording gestational age, weight of the mother. Data abstracted from prenatal records included information on weight gain, blood pressure and blood tests. - i).Pre assessment of weighing scale was done and rechecked by weighing standard 2500 g weight. ii).Weighing scale was checked for 0.00 reading. iii).Women were given instructions that they should stand erect facing forward and should stand on weighing scale without support or touching any object then finally the weight was recorded. From weight at registration and weight at delivery the difference was calculated and called weight gain during pregnancy. Height of the women was taken by using standard height measurement scale available in ANC clinic and categorized as per ICMR standards for heights of Indian women. (Horton companies mounted height scale was used to for taking height of each mother), Blood pressure (BP) measurements were checked by using standard Sphygmomanometer. Hemoglobin was assessed in pathology by fully automated analyzer of Sysmex, XS-800i and ERMA NC (PCE-210) companies and categorized as per WHO classification. BMI was calculated for all women and categorized as per WHO classification.
Data analysis: Data was analyzed in respect to the objectives of the study by using descriptive and inferential statistics.
Descriptive statistics: Frequency and percentage distribution was used to analyze the demographic data of the respondents
Inferential statistics: Chi-square (χ2) test was used to see an association with respect to maternal risk factors, computed mean, standard deviations (SD). ANOVA, Bonfferoni multiple comparison test, unpaired t test was used.
Results:
Distribution of Preterm, Term and Post Term babies according to Gestational Age [N= 365] |
| Gestational Age |
Frequency |
Percentage |
Preterm ( < 259 days) < 37 wks |
42 |
11.5 |
Term ( 259 to < 294) 37 to < 42 wks |
312 |
85.5 |
Post-term ( = 294 days ) =42 wks |
11 |
3.0 |
Total |
365 |
100.0 |
| *LMP - Not known 15 cases were excluded. |
Table 2: Distribution of babies According to Birth Weight and Gestational Age [N= 365] |
|
Birth Weight Groups in (g) |
|
Gestational Age
in Weeks |
1000-1499 |
1500-1999 |
2000-2499 |
25002999 |
3000+ |
Total |
28 to <32 |
2 |
0 |
0 |
0 |
1 |
3 |
66.7% |
.0% |
.0% |
.0% |
33.3% |
100.0% |
25.0% |
.0% |
.0% |
.0% |
1.0% |
.8% |
32 to < 37 |
3 |
8 |
16 |
10 |
2 |
39 |
7.7% |
20.5% |
41.0% |
25.6% |
5.1% |
100.0% |
37.5% |
72.7% |
20.8% |
6.0% |
2.0% |
10.7% |
Sub Total
(Preterm) |
5 |
8 |
16 |
10 |
3 |
42 |
74.40% |
20.50% |
41.00% |
25.60% |
38.40% |
100.00% |
62.50% |
72.70% |
20.80% |
6.00% |
3.00% |
11.50% |
37 to <42
(Term) |
3 |
2 |
60 |
153 |
94 |
312 |
1.0% |
.6% |
19.2% |
49.0% |
30.1% |
100.0% |
37.5% |
18.2% |
77.9% |
91.1% |
93.1% |
85.5% |
= 42
(Post-term) |
0 |
1 |
1 |
5 |
4 |
11 |
.0% |
9.1% |
9.1% |
45.5% |
36.4% |
100.0% |
.0% |
9.1% |
1.3% |
3.0% |
4.0% |
3.0% |
Sub Total
(Term+ Post-term) |
3 |
3 |
61 |
158 |
98 |
323 |
1.00% |
9.70% |
28.30% |
94.50% |
66.50% |
100.00% |
37.50% |
27.30% |
79.20% |
94.10% |
97.10% |
88.50% |
Grand Total |
8 |
11 |
77 |
168 |
101 |
365 |
2.2% |
3.0% |
21.1% |
46.0% |
27.7% |
100.0% |
100.0% |
100.0% |
100.0% |
100.0% |
100.0% |
100.0% |
The mean gestational age of 365 women was 274.1 days with SD of ±13.6 days. There were 42 (11.5%) preterm deliveries out 365 deliveries studied, 03 (0.8%) occurred before completing 32 weeks of gestation, 312 (85.5%) were term deliveries while 11 ( 3.0%) were post term deliveries occurring after 42 weeks of gestation. There was a significant association with gestational age and the birth weight of the baby. The birth weight increased with the increasing gestational period. The Pearson Correlation (r) =0.385, p<0.001 between gestation and the birth weight was statistically significant. To find out risk factors associated with prematurity, the term and post term deliveries were pooled and compared with preterm deliveries.
Table 3: Calorie and Protein intake as proportion of the individualized RDA and Mean and Mean Gestational Age and Proportion of Preterm births [N= 365] |
| Percentage Groups |
No. |
% |
Mean Gestational Age with ±SD in (g) |
No. of Preterm (%) |
χ2 and
p- value |
Correlation coefficient (r) with 95% CI |
% of Calorie intake (kcals) of Individualized Recommended Daily Allowance |
< 70 |
30 |
8.2 |
267.6± 18.4 |
9 (2.5) |
χ2 =29.249;
p < 0.001** |
(r) = 0.2527
95% CI = 0.1540 to 0.3464 ; P<0.001** |
70 to < 80 |
26 |
7.1 |
271.6± 14.6 |
5 (1.4) |
80 to < 90 |
37 |
10.1 |
269.0± 19.6 |
9 (2.5) |
90 to < 100 |
58 |
15.9 |
272.5± 12.6 |
9 (2.5) |
100 to < 110 |
66 |
18.1 |
274.6± 11.7 |
5 (1.4) |
110 to < 120 |
66 |
18.1 |
276.4± 10.2 |
3 (0.8) |
= 120 |
82 |
22.5 |
278.6± 10.3 |
2 (0.5) |
% of Protein intake (g) of Individualized Recommended Daily Allowance |
< 70 |
311 |
85.2 |
273.5± 14.2 |
41 ( 13.2) |
χ2 =5.885;
p = 0.208 |
(r) = 0.1361
95% CI = 0.03388 to 0.2355;
P=0.009** |
70 to < 80 |
37 |
10.1 |
278.4± 9.0 |
1 ( 2.7) |
80 to < 90 |
13 |
3.6 |
275.9± 8.0 |
0.0 |
90 to < 100 |
2 |
0.5 |
273.5± 12.0 |
0.0 |
100 to < 110 |
2 |
0.5 |
279.0± 1.4 |
0.0 |
110 to < 120 |
00 |
0.0 |
0.0 |
0.0 |
= 120 |
00 |
0.0 |
0.0 |
0.0 |
Calcium intake in (mg): |
< RDA |
329 |
90.1 |
273.9± 13.9 |
40 (12.2) |
χ2= 1.389;
p= 0.239 |
(r) = 0.1186
95% CI = 0.01617 to 0.2187;
P=0.0234** |
= RDA |
36 |
9.9 |
276.7± 10.3 |
2 ( 5.6) |
(Unpaired t= 1.182; p =0.238). |
Iron intake in (mg) : |
< RDA |
332 |
91.0 |
273.7± 14.0 |
42 (12.7) |
χ2 = 4.718;
p = 0.030** |
(r) = 0.1853
95% CI = 0.08420 to 0.02826 ;P=0.004** |
= RDA |
33 |
9.0 |
278.7± 6.9 |
0.0 |
(Unpaired t= 2.037 p =0.042) |
| RDA for sedentary type of work during pregnancy = 2250 kcals]; RDA for Moderate type of work during pregnancy = 2580 kcals] ; RDA for Heavy type of work during pregnancy = 3200 kcals 5, 6.7.8 ; * Not significant; ** Significant |
Proportion of Calorie Intake and Gestational Age: It was observed that 30 (8.2%) mothers consumed <70 % of kcals individualized RDA for calories. The mean gestational age of the babies born to mothers who were taking <70% kcal was lowest i.e. 267.6±18.4 as compared to those who were consuming higher proportion of calories. The higher proportion of preterm babies were delivered by the mothers consuming <70%, 80 to < 90%, 90 to <100% of calories compared to those consuming more. (χ2=29.249; p<0.001). There was significant correlation between gestational age and proportion of calorie intake of mothers (r) = 0.252; p < 0.001 with 95% CI of 0.1540 to 0.3464. (Table-3)
Proportion of Protein intake and Gestational Age: There were 311 (85.2%) mothers who consumed < 70% of the required protein. The mean gestational age of mothers who consumed < 70% of protein was lowest i.e. 273.5± 14.2 as compared to those who were consuming higher proportion of protein intake. The higher proportion of preterm babies i.e. 41(13.2%) were delivered by the mothers consuming <70% of proteins (χ2 = 5.885; p=0.208). There was significant correlation between gestational age and proportion of protein intake of mothers (r) = 0.136; p=0.009 with 95% CI of 0.03388 to 0.2355. The mean protein intake of 365 mothers was 70.7 gm with SD of 15.9 gm. (Table-3)
Calcium intake and Gestational Age: There was no significant association between calcium intake and gestational age or rate of preterm births. (Unpaired t= 1.182 p=0.238; χ2 =1.389; p =0.239)
Iron intake and Gestational Age: Higher daily iron intake of 35 mg or more among women was associated with longer gestational period (Unpaired t=2.037; p=0.042). There were no preterm births in this group of 33 women (χ2 =4.718; p =0.030) consuming 35 mg or more iron.
Weight at Registration of Mother and Gestational Age: The mean weight of the pregnant women at registration was 46.7 kg, with SD of 8.8 kg minimum being 31 kg and maximum of 74 kg. There was no significant difference between weight at registration and gestational age. (ANOVA F=0.287; p=0.835). There was apparently higher mean gestational age for the babies born to the mothers weighing in the weight range of < 40 and 45 to 50 kg as compared to the babies born to mothers with weight range of 40 to 45 kg and 50 to = 55 kg. Weight of mother at registration was not associated with the rate of preterm births. (χ2 = 5.320; p =0.150); (Table 4)
Height and Gestational Age: The mean height of the delivering women was 154.3 cm with a SD of 6.2 cm. Minimum height was 127.0 cm and maximum was 170.0 cm. There was no significant association between the height of mother and mean gestational age of babies. (ANOVA F = 0.645, p=0.666). There was no significant difference in the rate of preterm birth among different height groups of mothers, although an apparently higher rate of preterm births of 13.9% was observed for height of mother of 151-155 cm. (χ2 =1.947; p =0.856); (Table 4)
The minimum maternal weight before delivery was 40 kg and maximum was 87 kg. The mean maternal weight before delivery was 58.2 kg with a SD of 9.0 kg. The mean weight gain from registration to delivery was 11.5 kg with a SD of 2.6 kg and minimum weight gain was 5 kg the maximum gain in weight was 15.1 kg. There was an increase of 5 kg weight in one woman, who delivered a baby with 995 gm birth weight at 32 weeks of gestational age.
Weight Gain and Gestational Age: Weight gain during pregnancy and the mean gestational age of the baby and the proportion of preterm showed that there was a direct positive relationship between the weight gain during pregnancy and mean gestational age of the baby.[ANOVAF =4.821, p<0.003].With increasing weight gain during pregnancy, there was an increase in the mean gestational age. If the weight gain was lesser than <7.5 kg, the mean gestational age was lesser than 1.5 days. The rate of preterm was significantly lower when the weight gain was 12.5 kg or more and was associated with the lowest rate of preterm births i.e. 5.7% (χ2 =22.479; p< 0.001). The Bonferoni multiple comparison test revealed that among all comparisons the weight gain of = 12.5 Vs weight gain of 7.5 to < 10 kg; showed significant difference (p = 0.006) (Table 4)
Table 4: Anthropometric Indices and Gestational Age [N=365] |
| Anthropometric Indices |
No. |
% |
Mean Gestational Age ± SD (days) |
No. (%)
Preterm |
Weight at Registration in kg: |
|
< 40 |
83 |
22.7 |
274.8± 14.9 |
8 (9.6) |
40 to 45 |
101 |
27.7 |
273.8± 12.4 |
11 (10.9) |
45 to 50 |
67 |
18.4 |
275.1± 10.6 |
4 (6.0) |
50 to =55 |
114 |
31.2 |
273.5± 15.1 |
19 (16.7) |
Total |
365 |
100.0 |
274.1± 13.6 |
42 (11.5) |
(χ2 = 5.320; p =0.150); ANOVA F=0.287; p=0.835) |
Height of mother in cm |
= 145 |
22 |
6.0 |
276.7± 10.6 |
1 (4.5) |
146-150 |
85 |
23.3 |
274.5± 14.3 |
10 (11.8) |
151-155 |
108 |
29.6 |
272.3± 15.9 |
15 (13.9) |
156-160 |
100 |
27.4 |
274.8± 11.8 |
11 ( 11.0) |
161-165 |
36 |
9.9 |
274.8± 11.0 |
4 (11.1) |
> 165 |
14 |
3.8 |
275.6± 11.9 |
1 (7.1) |
Total |
365 |
100.0 |
274.1± 13.6 |
42 (11.5) |
χ2 = 1.947; p =0.856); ANOVA F= 0.645 ; p=0.666) |
Weight gain in kg |
< 7.5 |
34 |
9.3 |
270.2± 16.4 |
8 (23.5) |
7.5 to < 10 |
43 |
11.8 |
268.7± 18.8 |
12 (27.9) |
10 to < 12.5 |
96 |
26.3 |
274.0± 11.9 |
11 (11.5) |
= 12.5 |
192 |
52.6 |
276.1± 11.9 |
11 (5.7) |
Total |
365 |
100.0 |
274.1± 13.6 |
42 (11.5) |
(χ2 = 22.479; p < 0.001; ANOVA F= 4.821; p=0.003**) |
Table 5: Laboratory parameter, Mean Birth Weight and proportion of preterm [N=365] |
| Anemia (Hemoglobin level) at Registration in g% |
No. |
% |
Mean Gestational Age ± SD (days) |
No. (%)
Preterm |
Severe anemia |
12 |
3.3 |
276.1± 12.7 |
1 (8.3) |
Moderate anemia |
106 |
29.0 |
272.6± 15.4 |
15 (14.2) |
Mild anemia |
156 |
42.7 |
276.3±10.6 |
12 (7.7) |
No anemia |
91 |
24.9 |
271.9±15.4 |
14 (15.4) |
Total |
365 |
100.0 |
274.1±13.6 |
42 (11.5) |
(χ2 =4.419; p =0.220; ANOVA F= 2.666; p=0.048**) * Not significant ** significant |
Anemia during pregnancy and Gestational Age: There was a significant difference between the basic hemoglobin level of the mothers during first trimester and the gestational age (ANOVA F=2.666; p=0.048). The mean gestational age increased with increasing hemoglobin values. Those mothers with lesser than 7g% hemoglobin in the first trimester had 3.7% babies with mean gestational age 276.1 days. Anemia of any grade i.e. mild, moderate and severe, was not associated significantly with higher rates of preterm births (χ2 =4.419; p =0.220). A very high proportion of pregnant women i.e. 274 (75.0%) were anemic. The proportion of preterm was 30.2% as compared to 15.4 % in babies born to non- anemic mothers. However, this difference was not statistically significant. Mean Gestational age of babies of anemic mothers was 275 days and mean gestational age of non anemic mothers was 271.9 days. (Table 5)
Discussion
Present study has shown that current nutritional status of women as indicated by calorie intake is directly related preterm birth. Total caloric intake by sedentary workers of 2256.4 Kcal with SD ±377.1 was recorded in 28.8% of women while 66.3% of moderate workers were taking average 2431.3 Kcal with SD ±396.5 and total caloric intake by 4.9% heavy workers was 2083.7 Kcal with SD ± 384.1. When calorie intake of mothers was correlated with the preterm births, it was found that heavy workers delivered 33.3% pre term births. Similar findings have been observed by Chandra S. Metgud et.al[9] at Belgaum in rural Karnataka, India, who found a statistically significant relationship between the calorie intake (crude OR 4.9, 95% CI 1.7–14.1, p 0.003) and birth weight of the newborn when compared with protein intake (crude OR 2.1, 95% CI 1.2–3.7, p 0.007).[9] In the present study mean protein intake were 71.1 ± 15.8 g. Majority of mothers i.e. 273 (74.8%) had lesser protein intake than the RDA. Higher daily protein intake was associated with a significantly longer gestational period (p =0.028), and apparently lower proportion of preterm births (p =0.035). In a study conducted by Rama et al[10], a decrease in abortions, preterm deliveries and still births were reported with increase in dietary protein.[10]
There was no significant association between calcium intake and gestational period or rate of preterm births. (p =0.238; p=0. 239). The study conducted by Anisha M Durrani et al [11] in Aligarh city India reported that calcium consumption was found to be positively correlated with birth weight in the first (r=0.276), second (r=0.355) and third (r=0.421) trimesters. Similarly, significant correlations were found between adequate maternal calcium and vitamin D intake with birth weight and 1-min Apgar score of newborns by Rao et al [12] at Haryana. Gopalan C [6] at Hyderabad also found that the highest mean birth weight was observed among mothers consuming = 1000 mg/d of calcium.
In the present study, anemia of all grades i.e. mild, moderate and severe, in 1st trimester was significantly related to the gestational period (p< 0.048). Maternal anemia was not only responsible for maternal mortality but also associated with preterm birth in the study of Schultink W [13] Hyderabad, Pakistan. In the study conducted by Naila Baig-Ansari [14] in Pakistan, involving the University of Alabama, Birmingham, Alabama, USA, the incidence of LBW in women suffering from anemia during pregnancy was about 1.5-fold of those in normal pregnancies.
Conclusion
Proportion of calorie intake individually calculated by weight at registration and age of mother, protein intake as per weight of mother, iron intake by ICMR requirement, weight gain during pregnancy were strongly associated with the preterm births.
Recommendations:
-
It is essential to monitor weight gain in pregnancy and ensure at least 10 kg weight is gained during pregnancy. It would be very helpful if parameters are developed to know expected weight gain by 4,5,6 months and also during third trimester so that the mothers with inadequate weight gain can be identified and reasons related to nutritional intake, inadequate rest, hard work or morbidity could be identified as early as possible during antenatal period for corrective action and primary prevention of LBW and preterm births.
-
At the time of registration, weight of less than 40 kg, Anemia and < 4 meals per day, hard work can be identified and marked on ANC cards for possible remedial measures by health educations of the pregnant women and the family members.
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