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Risk status of pregnant women in rural areas of Belagavi: a cross sectional study

Global maternal morbidity and mortality rates remain unacceptably high. In 2015 it was estimated that around 3,03,000 women died during and following pregnancy and childbirth; deaths of which most could have been prevented and 99% of which occurred in developing countries. More than half of maternal deaths occur in subSaharan Africa and almost one third occur in South Asia. There are large disparities both between and within countries, between women with high and low income, and those living in rural versus urban areas. 1 The World Health Organisation estimates the maternal mortality ratio in developing countries at 239 per 100,000 live births (as opposed to 12 per 100,000 in developed countries). 2 As part of the Sustainable Development Goals, the target is to reduce the global maternal mortality ratio to less than 70 per 100,000 live births by 2030. 3 ABSTRACT

Pregnancies with a status of 'high-risk' account for a significant proportion of perinatal morbidity and mortality worldwide. 4 A high-risk pregnancy is defined as one in which any maternal or foetal factor which may adversely affect the outcome of the pregnancy. 4 Perinatal outcome can be influenced considerably by early detection of high risk pregnancies, appropriate planned antenatal management and timely referral to higher centres. 4 Routine assessment of risk status in pregnancy therefore represents an opportunity to improve levels of maternal morbidity and mortality, particularly in poor and rural areas. In view of the above facts, an attempt was made to assess the risk status of pregnant women in rural areas of Belagavi.

Study design:
Cross-sectional study.

Study setting
Primary Health Centre and surrounding subcentres at Kinaye field practice area of Department of Community Medicine, Jawaharlal Nehru Medical College, KAHER, Belagavi.

Study population
Pregnant women attending antenatal clinics under PHC during study period.

Sample size and methods
All pregnant women attending antenatal clinics during study period using universal sampling method.

Data collection
Data was collected through interviewing the study participants during the clinic using a pre-tested predesigned questionnaire, after obtaining informed written consent. The questionnaire was based upon a prenatal scoring system (proposed by Coopland et al at the University of Manitoba, 1977, modified for use in India by Dutta & Das). 5,6 This is a 32-item scoring system, classified into 4 subsections: 'reproductive history factors, past obstetrical history, present pregnancy factors, associated disease factors'. This scoring system has been assessed in several previous studies in rural India, and has been shown to be effective in predicting high risk pregnancies, correlating with perinatal outcomes. 7,8 Two items from the present pregnancy category of the original prenatal scoring system were omitted -namely 'prolonged labour' (in present pregnancy) and ´premature rupture of membranes'because they related to end stage of pregnancy only, and were therefore not applicable to participants of all trimesters. The classifications of low, moderate and high risk were adapted accordingly. Within the scoring system, 'abortion' was defined as spontaneous miscarriage, whereas induced miscarriage (i.e. termination of pregnancy) was classified under previous gynaecological surgery. 'Infertility' was defined as lack of conception after 2 years of trying to conceive without use of contraceptive methods. Previous 'prolonged/difficult labour' was defined as labour lasting more than 24 hours or instrumental delivery. 9 Foetal presentation was only recorded for participants in third trimester of pregnancy. 'Undernutrition' was defined as maternal weight below 45 kg at time of conception. 10 Hypertension was classified as current reading greater than 140/90 mmHg. Anaemia was classified as current haemoglobin concentration lower than 11 g/dl.
As well as the contents of the prenatal scoring system, the predesigned questionnaire included a section for sociodemographic details (age, religion, monthly household income), and a section for additional maternal characteristics which did not fall within the scoring system (trimester of pregnancy, current Body Mass Index, and gestational diabetes mellitus, hypothyroidism, or hyperthyroidism in current pregnancy). Body mass index (BMI) was calculated using the standard equation: BMI (kg/m 2 ) = Weight (kg)/height 2 (m 2 ), based on height and weight measurements taken on the day of clinic. Socioeconomic status was derived from household income per capita per month, according to latest scales of the modified B.G. Prasad's classification. 11 Height, weight, blood pressure, foetal presentation, haemoglobin concentration, and urine albumin were collected as per the routine antenatal clinic examination and investigations. Blood pressure was measured with a mercury sphygmomanometer on the right arm with subjects in sitting position. Hemoglobin estimation was done by using Sahli's method. Presence of polyhydramnios, intrauterine growth restriction or multiple pregnancy was ascertained from Ultrasound scan reports in the patients' handheld pregnancy records.

Inclusion criteria
Inclusion criteria were all patients with a positive urinary pregnancy test attending the antenatal clinic were included; Women of all ages and trimesters were included.

Exclusion criteria
Exclusion criteria were patients undergoing obstetric emergency needing urgent medical management were not included.

Data analysis
Data was coded & entered in Microsoft Excel software. Statistical analysis was done using SPSS version 21 statistical software. Categorical data was presented as percentage (%). Pearson's chi-square test and Spearman rank method were used to evaluate difference between groups for categorized variables.

Ethical considerations
The study was approved by the institutional ethics committee.

RESULTS
The study received 105 respondents.    (Table 3).   According to the prenatal scoring schedule, nine participants (8.6%) scored 0, and were classed as having a 'no risk' pregnancy. 31 (29.5%) scored 1-2 and were classed as low risk, 32 (30.5%) scored 3-4 and were classed as moderate risk, and 33 (31.4%) scored 5 or above and were classed as 'high risk' A total of 96 participants (91.4%) scored 1 or above and were classed as 'at risk' (either low, moderate or high) ( Table 4).
No statistically significant associations were found between risk status of pregnancy and religion and socioeconomic status (Table 7). Statistically significant association was found between risk status and underweight BMI, with 58.33% of the 24 underweight participants at moderate risk, and 33.33% at high risk (p<0.05). Statistically significant association was also found between risk status and hyperthyroidism; 100% of participants with hyperthyroidism were at high risk (p<0.05). However, given the fact that the total number of participants with hyperthyroidism was only two, it is difficult to justify this finding. No statistically significant associations were found between risk status and trimester of pregnancy, gestational diabetes mellitus, or hypothyroidism (Table 8).   Statistically significant negative correlation was found between risk score and body mass index. Statistically significant positive correlation was found between risk score and hyperthyroidism. No statistically significant correlations were found between risk score and trimester, gestational diabetes mellitus, or hypothyroidism respectively (Table 9).

DISCUSSION
The results of the present study found the prevalence of 'no risk' pregnancy to be 8.6%, low risk 29.5%, moderate risk 30.5%, and high-risk pregnancy 31.4%.
This can be compared to a previous study in Telangana, which used the same prenatal scoring system (modified by Dutta & Das) to calculate individual risk scores for 200 participants.45% participants were found to belong to low risk, 33% to moderate risk and 20 % to the high risk category. 7 This demonstrates a considerably different distribution of risk status than the findings of the present study. However, the study in Telangana was designed to be prospective, assessing association between high risk and pregnancy outcomes (namely perinatal mortality and birth asphyxia). It therefore only included participants of term gestation reporting to the labour room. 7 This represents a contrast to the present study which included participants of all trimesters, and as such used an adjusted cut-off value for high risk (omitting factors which related to end-stage pregnancy only). This may explain the difference in findings of risk prevalence.
Previous studies which included participants regardless of gestation yielded results which are more comparable. A cross-sectional study in rural Haryana which included 900 pregnant women of all trimesters found the same prevalence of high risk pregnancy as that found in the present study (31.4%). 12 Another cross-sectional study undertaken with 100 participants in rural Dharwad also found similar prevalence of high risk pregnancy (37%). 13 However the aforementioned studies used alternatives to the prenatal scoring system used in the present study, meaning different risk factors were assessed. Nor did they distinguish between low, moderate and high risk status. 12,13 In present study, the most common factors present in 'at risk' pregnancies were found to be undernutrition (42.1%), nulliparity (37.9%), and previous abortion (26.3%). The same factors were found to be most common in the high risk participants, of whom 57.6% scored points for undernutrition, 48.5% for nulliparity, and 39.4% for previous abortion. This is somewhat consistent with findings of the cross-sectional study in rural Dharwad, where history of ≥2 abortions was found to be second most common risk factor (29.7%) among the high-risk participants. However, the most common factor among high risk participants in this study was not undernutrition but maternal height <140cm (40.5%). The same prenatal scoring system used in the present study was not used in the Dharwad study, and as a result 'undernutrition' was not included in scoring, therefore making risk factors difficult to compare with those of the present study. 13 Previous studies have also demonstrated associations between risk status in pregnancy and various sociodemographic variables. In rural Dharwad, 45.2% of the participants in lower socioeconomic group (classes III, IV and V) were classified as high risk, as opposed to 23.6% of the upper socioeconomic group (classes I and II). 13 Similarly in the cross-sectional study undertaken in rural Haryana, prevalence of high risk pregnancy was significantly higher in lower socioeconomic groups than in upper socioeconomic groups (33.4% and 19.7% respectively). 12 However, in the present study, no statistically significant associations were found between risk status and the socio-demographic variables recorded (namely age, religion and socioeconomic status). This is likely due to insufficient sample size, which represents a significant limitation of the present study.
Upon analysis of other maternal characteristics which were not included in the prenatal scoring system, statistically significant associations were found between risk status and underweight BMI, as well as risk status and hyperthyroidism. Additionally, negative correlation was found between risk score and BMI, and positive correlation between risk score and hyperthyroidism. However, due to low sample size, the total participants scoring for hyperthyroidism were only two (both of whom were at high risk); this association would therefore need further justification.
The association between risk score and underweight BMI represents a more useful finding of the present study. Use of 'Undernutrition' in the prenatal scoring system was defined by pre-conceptional weight <45 kg. Undernutrition proved to be the most common risk factor scored for among 'at risk' participants (affecting 42.1% of those at risk, and 57.6% of those at high risk), thus representing a very important consideration for the study population. Measurement of current height and weight, in addition to pre-conceptional weight estimation, allowed assessment of up to date body mass index for participants. Given that normal BMI parameters are not designed to apply to pregnant women, BMI <18.5 during any trimester of pregnancy represents an even stronger indication of underweight than in the normal adult population. 14 Maternal undernutrition has been found to be of highest prevalence in South Asian countries, and has been established in previous studies as an important contributor to adverse pregnancy outcomes; in particular low birth weight and neonatal mortality. 14 The present study helps to confirm the importance of undernutrition as a risk factor for high risk pregnancy in rural areas of Belagavi which is likely also to be applicable in many other districts across India.

CONCLUSION
The present study suggested that almost one third of the study participants were at 'high risk' of adverse outcome, and that the pregnancies of almost all participants were to some degree 'at risk'. Maternal undernutrition appeared to be an important factor in high risk pregnancy among participants in this study area.
The prenatal scoring system used in the present study offers a simple and efficient method for risk status assessment in pregnant women, suited for use in antenatal clinics in rural areas of India, and suitable for women of all trimesters. Efforts should be made to promote routine use of a single scoring system more widely across