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The study of anemia in gestational diabetes mellitus.

INTRODUCTION: GDM is a state of Glucose intolerance diagnosed during pregnancy and affects 114% pregnancy in different population. The incidence has been increasing in past 20 years. (1,2) GDM increases both short and long term complications in both mother and child. GDM increases risk of developing Type2 Diabetes in later life of both mother and child. High iron load and disorders of iron metabolism have been associated with an increased risk of diabetes Eg: Hemochromatosis patients develop diabetes in 30-60%. (3,4) Iron binding medication in such patients are shown to prevent diabetes. (5)

High Hb levels in pregnancy has been reported to be individual risk factor for GDM and low Hb levels and Anemia have shown to result in lowering the risk of GDM. Most such studies are from outside Indian country. Hence our study aims at investigating the possible association between Anemia and GDM in South Indian Women.

Aims and Objective:

* To investigate possible association between Anemia and Gestational Diabetes Mellitus (GDM).

MATERIALS AND METHODS:

Study Design:

* A total of 130 patients were screened for study out of which 100 were eligible for study. Demographic data, past obstetric history, detailed clinical examination including height, weight and BMI were taken. Blood sugars, HbA1c, complete blood counts including peripheral smear were estimated.

Place of study:

* The data for this study was collected from 100 GDM patients from out-patient and In-patient of Vani Vilas hospital and Bowring & Lady Curzon hospital, BMC & RI, Bangalore.

Time period:

* November 2012 to July 2013

Inclusion criteria:

* Either newly detected GDM patients or on follow up

* Between age group of 18-35years.

Exclusion criteria:

* Age>35years

* Renal impairment

* Thyroid dysfunction

* Overt diabetes either type 1 or 2.

* Statistical methods: Descriptive and inferential statistical analysis has been carried out in the present study. Results on continuous measurements are presented on Mean [+ or -] SD (Min-Max) and results on categorical measurements are presented in number (%). Significance is assessed at 5 % level of significance.

* Students t test (two tailed, independent) has been used to find the significance of study parameters on continuous scale between two groups Inter group analysis) on metric parameters. Chi-square/ Fisher Exact test has been used to find the significance of study parameters on categorical scale between two or more groups.

* Statistical software: The Statistical software namely SAS 9.2, SPSS 15.0, Stata 10.1, Med Calc 9.0.1, Systat 12.0 and R environment ver.2.11.1 were used for the analysis of the data and Microsoft word and Excel have been used to generate graphs, tables etc.

RESULTS: A total of 100 GDM patients were investigated. The mean age of the patient was 26.09 [+ or -] 3.4years.The overall prevalence of Anemia was 7.0%.The mean HbA1c was 7.80 [+ or -] 0.63. Mean haemoglobin was 12.01 [+ or -] 1.29 g/dl and it was positively associated (r=0.75) with impaired glucose metabolism. The mean blood glucose at 0hrs and 2hrs after was 158.73 [+ or -] 35.97 and 274.40 [+ or -] 67.04 mg/dl respectively. Haemoglobin level was highly correlating and statistically significant with prevalence of GDM (P<0.05).

Our study found that the incidence of anemia in GDM patients was considerably lower than the incidence in normal pregnancy. Those patients who had anemia, their peripheral smear examination showed majority to be Normocytic Normochromic Anemia. Other observations in our study revealed that younger age was associated with Anemia; BMI was not significantly associated with GDM.

Statistical Analysis:
Table 1: Age distribution of patients studied

Age in years   No. of patients     %

19-24                37          37.0
25-29                46          46.0
30-34                17          17.0
Total                100         100.0


Mean [+ or -] SD: 26.09 [+ or -] 3.38
Table 2: Region distribution of patients studied

Region   No. of patients     %

Rural           1           1.0
Urban          99          99.0
Total          100         100.0

Table 3: BMI (kg/[m.sup.2]) distribution of patients studied

BMI (kg/[m.sup.2])   No. of patients      %

<23                        26           26.0
23-30                      65           65.0
>30                         9            9.0
Total                      100          100.0

Mean [+ or -] SD: 26.23 [+ or -] 3.77

Table 4: Previous bleeding of patients studied

Previous bleeding   No. of patients     %

No                        97          97.0
Yes                        3           3.0
Total                     100         100.0

Table 5: No. of deliveries

No. of deliveries   No. of patients     %

0                          2           2.0
1                         76          76.0
2                         14          14.0
3                          4           4.0
4 & above                  4           4.0
Total                     100         100.0

Table 6: Incidence of anemia in patients studied

Anemia    No. of patients     %

Absent          94          94.0
Present          6           6.0
Total           100         100.0

Table 7: Age distribution according to incidence of Anemia in
patients studied

Age in years          Anemia            Total

               No anemia    Anemia

19-24          34(36.2%)    3(50%)     37(37%)
25-29          44(46.8%)   2(33.3%)    46(46%)
30-34           16(17%)    1(16.7%)    17(17%)
Total          94(100%)    6(100%)    100(100%)

Lower age is positively associated with incidence of anemia with
p=0.117

Table 8: BMI (kg/[m.sup.2]) with incidence of anemia

BMI (kg/[m.sup.2])          Anemia            Total

                     No anemia    Anemia

<23                  25(26.6%)   1(16.7%)    26(26%)
23-30                56(59.6%)   5(83.3%)    61(61%)
>30                  13(13.8%)    0(0%)      13(13%)
Total                94(100%)    6(100%)    100(100%)

BMI is not statistically associated with incidence of anemia
with p=0.710

Table 9: P Smear findings of patients studied

P Smear   No. of patients     %

MCHC             3           3.0
NCNC            97          97.0
Total           100         100.0

Table 10: P. Smear findings with incidence of anemia

P Smear           Anemia          Total

          No anemia   Anemia

MCHC        0(0%)     3(50%)      3(3%)
NCNC      94(100%)    3(50%)     97(97%)
Total     94(100%)    6(100%)   100(100%)

Table 11: Baseline variables according to incidence of anemia in
patients studied

                                          Anemia

                           No anemia                Anemia

Age in years          26.09 [+ or -] 3.37     26.17 [+ or -] 3.87
BMI (kg/[m.sup.2])    26.29 [+ or -] 3.86     25.31 [+ or -] 1.76
Pulse rate           80.28 [+ or -] 10.32    80.33 [+ or -] 13.35
Blood pressure       118.82 [+ or -] 8.28    120.10 [+ or -] 5.20
Hb                    12.21 [+ or -] 0.99     8.93 [+ or -] 1.50
FBS                  159.85 [+ or -] 35.95   141.17 [+ or -] 34.52
PPBS                 283.81 [+ or -] 59.44   238.00 [+ or -] 49.65
HbA1c                 7.42 [+ or -] 0.79      7.17 [+ or -] 0.82

                             Total            P value

Age in years          26.09 [+ or -] 3.38      0.955
BMI (kg/[m.sup.2])    26.23 [+ or -] 3.77      0.540
Pulse rate           80.28 [+ or -] 10.45      0.990
Blood pressure       118.90 [+ or -] 8.11      0.710
Hb                    12.01 [+ or -] 1.28    <0.001 **
FBS                  158.73 [+ or -] 35.97     0.219
PPBS                 281.06 [+ or -] 59.69    0.068+
HbA1c                 7.41 [+ or -] 0.79       0.450

Table 12: Correlation of Gestational DM with incidence of anemia

GDM                 Anemia          Total

        No anemia     Anemia

No      94(94.00%)       0        94(94.0%)
Yes         0        6(100.0%)     8(8.0%)
Total   94(100.0%)   6(100.0%)   100(100.0%)

GDM is significantly associated with incidence increased Hb with
P<0.001 **


DISCUSSION: In this study we investigated the possible relation between Anemia and GDM. To our knowledge there are no studies from South India in this regard. We found that the incidence of anemia specifically Microcytic Hypochromic Anemia was considerably lower in GDM women compared to Non GDM pregnancy.

In a somewhat similar study Annika Helinet al (6) discovered that women with high dietary iron intake and high Hb had increased risk of GDM. But the study didn't include Indian women. Similarly Qiuet al (7) demonstrated an association between high Heme Iron intake during pregnancy and the risk of GDM.

Iron is a highly reactive component with a possibility to participate in harmful reactions. (8) Iron excreted from human body is with very limited mechanism and thus intake of iron is highly regulated according to body needs. (9)

Iron could interfere in Glucose metabolism by following possible mechanism.

* Iron decreases insulin secretion and metabolism in liver which leads to peripheral hyperinsulinemia. (10)

* Iron overload results in oxidative stress in pancreatic (3-cells that leads to destruction of Islet cells and thus decreases insulin secretion. (11)

CONCLUSION: Our study suggests that incidence of anemia especially Microcytic Hypochromic Anaemia is considerably lower in GDM. These finding suggests that routine supplementation of iron irrespective of Hemoglobin (Hb) levels should be reconsidered in risk group women and iron supplements to be given only to women who has anemia due to Iron deficiency anemia, though studies on a larger group is warranted.

DOI: 10.14260/jemds/2014/2761

REFERENCES:

(1.) American Diabetes Association Diagnosis and classification of diabetes mellitus. Diabetes Care2012; 35 (Suppl 1):S64-71.

(2.) Ferrara A. Increasing prevalence of gestational diabetes mellitus: a public health perspective. Diabetes Care 2007; 30 (Suppl 2): S141-6.

(3.) Ford ES, Cogswell ME. Diabetes and serum ferritin concentration among U.S. adults. Diabetes Care1999; 22: 1978-83.

(4.) Powell LW, Yapp TR. Hemochromatosis. Clin Liver Dis 2000; 4: 211-28.

(5.) Fernandez-Real JM, Lopez-Bermejo A, Ricart W. Iron stores, blood donation, and insulin sensitivity and secretion. ClinChem 2005; 51: 1201-5.

(6.) Helin A, Kinnunen TI, Raitanen J, Ahonen S, Virtanen SM, Luoto R. Iron intake, haemoglobin and risk of gestational diabetes: A prospective cohort study. BMJ Open. 2012; 2: e001730.

(7.) Qiu C, Zhang C, Gelaye B, et al. Gestational diabetes mellitus in relation to maternal dietary heme iron and nonheme iron intake. Diabetes Care 2011; 34: 1564-9.

(8.) Papanikolaou G, Pantopoulos K. Iron metabolism and toxicity. Toxicol Appl Pharmacol 2005; 202:199-211.

(9.) Andrews NC. Disorders of iron metabolism. N Engl J Med 1999; 341: 1986-95.

(10.) Fernandez-Real JM, Lopez-Bermejo A, Ricart W. Cross-talk between iron metabolism and diabetes. Diabetes 2002; 51: 2348-54.

(11.) Cooksey RC, Jouihan HA, Ajioka RS, et al. Oxidative stress, beta-cell apoptosis, and decreased insulin secretory capacity in mouse models of hemochromatosis. Endocrinology 2004; 145: 5305-12.

(12.) Nilufar Islam, Saleha Begum Chowdhury. Serum Ferritin snd Gestational Diabetes Mellitus: A Case control study. Ibrahim Card Med J. 2011; 1(2):15-19.

(13.) Lao TT, Ho LF. Impact of iron deficiency anemia on prevalence of gestational diabetes mellitus. Diabetes Care 2004; 27: 650-6.

(14.) Chen X, Scholl TO, Stein TP. Association of elevated serum ferritin levels and the risk of gestational diabetes mellitus in pregnant women: the Camden study. Diabetes Care 2006; 29: 1077-82.

AUTHORS:

[1.] Srinivasa V.

[2.] Nagaraja B. S.

[3.] G. Chandra Mohan

[4.] Akila V.

[5.] Prakash Kikker Gowdaiah

PARTICULARS OF CONTRIBUTORS:

[1.] Associate Professor, Department of General Medicine, Bangalore Medical College and Research Institute, Bangalore.

[2.] Professor, Department of General Medicine, Bangalore Medical College and Research Institute, Bangalore.

[3.] Post Graduate, Department of General Medicine, Bangalore Medical College and Research Institute, Bangalore.

[4.] Post Graduate, Department of General Medicine, Bangalore Medical College and Research Institute, Bangalore.

[5.] Associate Professor, Department of General Medicine, Bangalore Medical College and Research Institute, Bangalore.

NAME ADDRESS EMAIL ID OF THE CORRESPONDING AUTHOR:

Dr. G. Chandra Mohan, Room No. 202, 2nd Floor, BMCRI Mens PG Hostel, Hospital Road, Shivajinagar, Bangalore-560001.

Email: drgchandramohan@gmail.com

Date of Submission: 12/05/2014. Date of Peer Review: 13/05/2014. Date of Acceptance: 30/05/2014. Date of Publishing: 07/06/2014.
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Title Annotation:ORIGINAL ARTICLE
Author:Srinivasa, V.; Nagaraja, B.S.; Mohan, G. Chandra; Akila, V.; Gowdaiah, Prakash Kikker
Publication:Journal of Evolution of Medical and Dental Sciences
Date:Jun 9, 2014
Words:1894
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