Monthly Archives: February 2022

Proportion of High Risk Mothers Attending Antenatal Clinic (ANC), PGIMER, Chandigarh 2018-20

DOI: 10.31038/IJNM.2022311

Abstract

Introduction: Pregnancy with high risk conditions is threatening the life of the mother as well as fetus. Each year, globally 529,000 women and girls die due to complications associated with pregnancy. Most of the complications are preventable with preventive measures. So, all the pregnant mothers should be evaluated for the high risk factors. This study assessed the proportion of high risk mothers in Antenatal clinic OPD PGIMER Chandigarh.

Aim: To assess the proportion of high risk mothers.

Material and method: Pre-experimental design was used where total 200 antenatal mothers were enrolled by purposive sampling technique. Data were collected by using interview schedule in the period of July to December 2019. An assessment proforma were used for the assessment of antenatal mothers with high risk conditions regarding maternal and fetal outcome.

Results: Finding of the study shows that mean age of high risk women were 28.6 years of age, attained menarche at the age of 13 years of age. Majority (63%) of the mothers belongs to Hindu family. More than 60% of the high risk mothers were having Anemia followed by Hypothyroidism (57.5%), Gestational diabetes mellitus (28.5%), Gestational Hypertension (15%), Previous history of caesarean section (14.5%), Age ≥35 years (8.5%), Rh negative mothers (5.5%), Height <145 cm (3.5%).

Conclusion: It is concluded that highest percentage of Antenatal women (63%) were with anemia followed by 57.5% with Hypothyroidism.

Keywords

Gestational diabetes mellitus, Gestational hypertension, High risk mothers

Introduction

Pregnancy is an inimitable, stirring, and joyful time in a women’s life as it express the woman’s incredible, innovative and fostering powers while providing a link to the future. It brings a new sense to the thought of beauty and this time a woman cherishes with enormous joy and anticipation. The emotion of carrying in a little soul within in her is glorious. A baby fills a peace in the mother’s heart that she never knew was empty [1]. Each week of pregnancy brings with a new changes and thoughts that may require some explanations and hold up to the pregnant woman. It is the period during which a baby is in the mother’s womb for about 280 days. Progression of both physiological and psychological changes occur during pregnancy [2]. A pregnant women passes through period of pregnancy, labor and puerperium, it is important to provide antenatal, Intranatal and postnatal care. The year 2016 and 2030, is considered as the Sustainable Development Goals, where the target is to reduce MMR to less than 70 per 100 000 live births globally [7]. According to study, there is 20 -30% high risk pregnancies in India which leads to 75% of perinatal mortality and morbidity. So, for the reduction of maternal mortality, it is necessary to detect high risk pregnancy and their management in early stage [8]. High risk factors includes obstetric factors- Grand multipara, Age less than 18 years and more than 35 years, Height less than 145 cm, multipara with bad obstetric history like (loss of baby, cesarean section, Hypertension in previous pregnancy, recurrent premature labour and abortion, Intrauterine growth retardation), case of disproportion, Malpresentation, multiple pregnancy, obstetric complications includes hemorrhage during pregnancy (threatened abortion, Antepartum hemorrhage), pregnancy induced hypertension (Preeclampsia, eclampsia), high risk fetus (premature labor, RH incompatibility fetus, post maturity, intrauterine growth retarded fetus). Medical factors includes (anemia and malnutrition, cardiac diseases (pulmonary tuberculosis, hepatitis, syphilis, psychiatric disorders, thyroid disorders and others), social factors include unwed pregnancy, no or less than 3 antenatal checkup or low socioeconomic group. In western countries this incidence of high risk pregnancy comes to about one third in all the pregnancies. This incidence can be seen at least double numbers, because of anemia, under nutrition, poor social factors and parity [3]. Each pregnancy has three trimesters. First trimester is first 12 weeks of pregnancy, second trimester starts from 13 weeks to 28 weeks and third trimester starts from 29 weeks to 40 weeks of pregnancy. The first trimester is the most essential for the development of a fetus. A women’s body goes through many changes during the first 12 weeks of gestation. Body structure and organ systems of the baby develop during this period. Most miscarriages and birth defect can be seen during this period [4]. During 2nd trimester, nausea and vomiting usually resolve, there are fewer complications can occur like pregnancy induced hypertension, diabetes mellitus, Oligohydromnia, Polyhydromnia, anemia, cardiac diseases, abortion. During third trimester, various complications can arise like Gestational diabetes, preeclampsia, preterm labour, premature rupture of membrane, intrauterine growth retardation; malpresentation [5]. High risk pregnancy refers to pregnancy where complications are faced by the mother and her unborn child and also it will affect the life of both mother and baby. Nesbitt, 1969 scored high risk pregnancy under eight factors on initial history, physical and laboratory examinations at the time of booking. These factors were age of the mother, race and marital status, parity, past obstetric history (abortions premature, fetal death, neonatal death, and congenital anomaly), medical and obstetric history and nutrition (systemic illness, specific infections, and diabetes), Rh problem, social and economic history, emotional survey. Each factor was attached penalty points 0.5.10, 20, 30. The total score of all eight categories were subtracted from a potential ideal score of 100; the score lying at or below 70 was high risk and above 70 was low to moderate risk. The outcome of pregnancy on the point of abortion, premature birth, low birth weight, prenatal complication, labour complication, perinatal mortality, neonatal morbidity and poor outcome were identified with high percentage with high risk scores. However, this score did not include risks developed during ongoing pregnancy and delivery. Currently, comprehensive risk scoring is made on initial score, continuing pregnancy and labour risk score, postpartum, maternal and neonatal risk monitoring [3]. Pregnancy checkup is necessary for at least ten times in case of high risk pregnant women and five times in case of normal pregnancies [6]. Prenatal assessment and screening of high risk cases through antenatal assessment, review lab orders/investigations, obtaining Ultrasonography report, identification of high risk and follow up prevent the complication of high risk pregnancy.

Objective

To assess the prevalence of high risk mothers in Antenatal clinic OPD PGIMER Chandigarh.

Methodology

Study design was pre-experimental. Sample was selected by using purposive sampling technique. Data were collected by using interview schedule in the period of July to December 2019. Antenatal women with high risk conditions were approached during their clinical visit in antenatal clinic, outpatient department (OPD). women were informed about the aim of the study and written consent was obtained. A structured interview schedule was used to gather information regarding identification data. An assessment proforma were used for the assessment of antenatal mothers with high risk conditions regarding maternal and fetal outcome. Content validity of the tool and protocols was confirmed for the completeness, content and language clarity by the Guide, Co-guides and experts from National Institute Of Nursing Education (NINE), and Department Of Obstetrics And Gynecology. Ethical approval was taken from institute ethics committee, PGIMER, Chandigarh vide no. NK/5163/Msc/10. A written Informed consent was obtained from the participants. Data was analyzed using descriptive statistics.

Results

Table 1a depicts the Sociodemographic profile of antenatal women with high risk conditions. Majority of the women with high risk conditions were in age group of 26-30 years resulting in the mean age of 28.65 ± 4.28. Majority of antenatal mothers were educated up to secondary. More than 60% of the antenatal women were Hindu, belongs to joint family and lived in urban area. Most of the antenatal women were vegetarian and per capita income between Rs 3504-7007.

Table 1a: Sociodemographic profile of Antenatal mother with High risk conditions.

Variables

Antenatal mother with high risk conditions (N=200)

f (%)

Age(years)

20-25

26-30

31-34

≥35

 

51(26)

87(44)

45(22)

17(8)

Educational status

Primary

Secondary

Graduate

Postgraduate

 

7(3)

 92 (46)

 48(24)

 53(27)

Religion

Hindu

Muslim

Sikh

 

126(63.0)

9(4)

65(33)

Per capita income(Rs)

<1050

1051-2101

2102-3503

3504-7007

7008 and above

 

2 (1.0)

31 (15)

55(28)

60(30)

52(26)

Type of family

Nuclear

Joint

 

72(36.0)

128(64.0)

Habitat

Urban

Rural

 

126(63.0)

74(37.0)

Dietary habits

Vegetarian

Non vegetarian

 

155(77.5)

45 (22.5)

Age Mean ± SD=28.65 ± 4.28; Range=20-45.
Per capita income Mean ± SD =5514.75 ± 4133.48; Range=1000-25000.

Table 1b shows the menstrual and obstetric profile of antenatal mothers with high risk conditions. Majority of women attained menarche at the age of 13 years, having regular menstrual periods and duration of menstruation more than 3 days. Majority of the women had marriage between the age 18-27 years and 71.5% had duration of marriage ≤5 years. Majority of antenatal women were primigravida and had history of one live birth. 77% of the antenatal women were having gestation between 29-42 weeks and 23% were having gestation 13-28 weeks. 2 out of 200 antenatal women were having the history of Post partum haemorrhage (PPH) in previous pregnancy.

Table 1b: Menstrual and Obstetric profile of Antenatal mothers with High risk conditions.

Variables

Antenatal mother with high risk condition (N=200) f (%)

 Age at menarche (years)

12

13

14

 

 37 (18.5)

 153 (76.5)

 10 (5.0)

Menstrual pattern

Regular

Irregular

 

177(88.5)

23(11.5)

Duration of menstruation(days)

≤ 3 days

>3 days

 

 66(33.0)

 134(67)

Age of marriage (years)

<18

18-27

28-35

 

11 (5.5)

152(76.0)

37 (18.5)

Duration of marriage (years)

5

6-10

11-15

>15

 

143 (71.5)

40 (20.0)

12(6.0)

5(2.5)

Gravida

Primigravida

Multigravida

 

115(57.5)

85(42.5)

Live birth

1

2

 

34(17.0)

7(4)

Period of gestation

13-28 weeks

29-40 weeks

 

46(23.0)

154 (77.0)

Previous history of PPH

 2(1.0)

Age of marriage Mean ± S.D =23.98 ± 3.582; Range: 16-35.

Table 1c depicts clinical profile of antenatal women with high risk conditions. More than 50% of the antenatal mother had Hemoglobin level (Hb) less than 11 gm/dl and TSH level more than normal. Less than 8% of the antenatal women were Rh-ve, blood pressure more than 140/90 mm of hg, presence of albumin and ketone in urine. Only Three percent of the antenatal mother had HbA1c more than normal. Nearly one third of the antenatal women had fasting blood sugar level more than 95 mg/dl and post-prandial more than 126 mg/dl.. Further table, shows that 31 or less than 31 % having pylectesis, ventricular septal defect, ventriculomegaly, choroid plexus cyst, fetal growth restriction based on ultrasound finding.

Table 1c: Clinical profile of Antenatal mother with High risk conditions.

Variables

Antenatal mothers with high risk conditions (N=200)

 f (%)

Blood group

Rh +ve

Rh –ve

 

189(94.5)

11(5.5)

Blood pressure

systolic

<140 mm of hg

>140 mm of hg

Diastolic

<90 mm of hg

>9 0mm of hg

 

 

195(97.5)

5(2.5)

 

186(93)

14(7)

Hb%

< 11 gm /dl

>11 gm/dl

 

126(63.0)

 74(37.0)

Blood sugar level

FBS(<95 mg/dl)

(≥95 mg/dl)

PPBS (<126 mg/dl)

(≥126 mg/dl)

HbAIc

Normal(<5.6)

Abnormal (≥5.6)

not done

 

140(70)

60(30)

 151(75.5)

49(24.5)

 

 51(25.5)

6(3.0)

143(71.5)

Urine testing

Presence of albumin

Presence of ketone

 

4(2.0) 10(5.0)

TSH level

Normal

abnormal

 

40(35.0)

75(65.0)

 Based on ultrasound findings N=13

Ventriculomegaly

2 (15)

Ventricular septum defect

1 (8)

Hydronephrosis

2 (15)

Choroid plexus cyst

3 (23)

Pylectesis

4 (31)

Fetal growth restriction and oligohydromnias

1 (8)

Table 2 illustrates the proportion of antenatal mother with high risk conditions. 63% of antenatal women had Anaemia followed by Hypothyroidism (57.5%), previous history of abortion (30%), Gestational diabetes mellitus (28.5%), Gestational Hypertension (15%), Previous history of caesarean section (14.5%), Age ≥35 years (8.5%), Rh negative mothers (5.5%), previous history of preterm baby (5%), Height <145 cm (3.5%), Oligohyramnios (3%), placenta previa (2%), Polyhydramnios (1%).

Table 2: Proportion of antenatal mother with high risk conditions.

Variables

Antenatal mother with high risk conditions (N=200)

f (%)

Height <145 cm

 7 (3.5)

Age ≥35 years

 17(8.5)

Rh-ve mothers

 11(5.5)

Previous history of pre-term baby

10 (5.0)

Previous history of abortion

60(30.0)

Previous history of LSCS

29(14.5)

Anaemia

126 (63.0)

Gestational Hypertension

30(15.0)

Gestational diabetes mellitus

57 (28.5)

Hypothyroidism

115(57.5)

Placenta previa

4 (2.0)

Oligohydromnia

5(3)

Polyhydromnia

1 (1)

Gestational diabetes mellitus with Anaemia

21(10.5)

Hypothyroidism with GDM with Anaemia

 12(6)

Hypothyroidism with Polyhydromnia with Anaemia

1(.5)

Hypertension with Placenta previa

1(0.5)

Hypertension with Anaemia

8(4)

Hypothyroidism with Anaemia

41(20.5)

Hypothyroidism with Gestational hypertension with Anaemia

3(1.5)

Hypothyroidism with Gestational hypertension

1(0.5)

Hypothyroidism with Oligohydromnias with Anaemia

1(0.5)

Hypertension with oligohydromnias

1(0.5)

Hypothyroidism with Gestational diabetes mellitus

5(2.5)

Hypothyroidism with Gestational hypertension with GDM

3(1.5)

Hypothyroidism with GDM with Gestational hypertension with Placenta previa with Anaemia

1(0.5)

Hypothyroidism with GDM with Gestational hypertension+Anemia

4(2)

Gestational Hypertension with oligohydromnias with Placenta previa with anaemia

1(0.5)

*Number is more because of more than one high risk conditions.

Discussion

High risk pregnancy can affect the health of mother or baby and complications are faced by the mother and her unborn child. If initially detection and effective management of high risk pregnancy can considerably be helpful for the reduction of maternal and neonatal mortality and morbidity rate. Present study was conducted with the objective to assess the proportion of high risk mothers. Two hundred women who fulfilled the inclusion criteria were chosen as subjects from Antenatal OPD, Obstetrics and Gynecology department of PGIMER, Chandigarh. The study was conducted from the month of July to august 2019. The collected data was analyzed using SPSS version 2.0, descriptive statistics were used for analyzing the data. Present study exhibit that 30% of the mother had history of abortion, history of caesarean section (14.5%) and 8.5% were elderly gravida. Findings are almost similar with the study conducted by Jaideep et al. [7], Kambaba Nazi Michel [8] found high risk mothers with history of abortion (27%), age ≥35 years (5.5%) and history of caesarean section (13.6%). They recommended that carefully monitoring is important for high risk women to avoid the occurrence of maternal mortality. Our study Shows that majority of the high risk mothers were having Anemia followed by Hypothyroidism, Gestational diabetes mellitus, Gestational Hypertension, Previous history of cesarian section, Age ≥35 years, Rh negative mothers, Height <145 cm. Kabamba Nzaji Michel et al. found that majority of high risk factors are history of maternal infection (18.5%), unexplained fetal or neonatal death antecedent (12.4%) [8]. Jaideep et al. also found the high risk factors. 59.8% were having bad obstetric history, 4% were having pregnancy induced hypertension, 3.2% were RH negative [7].

References

  1. Introduction to Pregnancy – Pregnancy [Internet]. [cited 2019 Feb 3].
  2. High-risk pregnancy. In: Wikipedia [Internet]. 2019 [cited 2019 Feb 3].
  3. Dawn CS (1986) Rule of Ten MCH care and education, uterine maturity score, textbook of obstetrics current edition Calcutta.
  4. What are symptoms of complications during the first trimester of pregnancy? | 1st Trimester Of Pregnancy [Internet]. Sharecare. [cited 2019 Feb 10].
  5. The Second Trimester of Pregnancy: Complications [Internet]. [cited 2019 Feb 10].
  6. Maternal mortality [Internet]. [cited 2019 Feb 6].
  7. Jaideep KC, Prashant D, Girija A (2017) Prevalence of high risk among pregnant women attending antenatal clinic in rural field practice area of Jawaharlal Nehru Medical College, Belgavi, Karnataka, India. International Journal of Community Medicine And Public Health. 28: 1257-1259.
  8. Michel KN, Ilunga BC, Astrid KM, Blaise IK, Mariette KK, et al. (2016) Epidemiological Profile of High-Risk Pregnancies in Lubumbashi: Case of the Provincial Hospital Janson Sendwe. Open Access Library Journal. 3:1.

Consequences of the COVID-19 Pandemic: A Study from India

DOI: 10.31038/PSYJ.2022413

Abstract

A study was carried out in India considering the consequences, which could have been faced by people due to the first wave of COVID-19 pandemic 2020. Data collected online through questionnaire using the snow ball sampling technique from 400 respondents from 13 States of India was considered. The questionnaire contained total 17 negative and positive items related to the consequences/outcome of the pandemic, which could also psychologically influence people unfavourably and favourably. The responses were scored to work out the total consequences score. The data was analyzed using Factor Analysis and Odds Ratio test and interpreted as proportion and scores. The results of the consequences score show that majority of the respondents have faced medium level of consequences, while some of them faced low consequences only. Negative consequences such as mental stress, income/job loss, less social interaction, increase in health problems, unrest or quarrel in the family, social interaction/transportation/recreation/capability of old people to support themselves/health care for medical problems being affected, work from home not helpful, and less reduction in family expenses during the pandemic have been observed under the study. Positive consequences of the pandemic such as reduced pollution and better environmental conditions due to lock down, lock down time used for learning agriculture/fisheries, and increase in time spent with family are also evident. Factor analysis shows that age, education, and no. of family members of the respondents explain 69.9% of the variability in their total consequences score. Odds ratio reveals that people aged more than 40 years, with PG and Degree qualifications, and having more than 4 family members faced less COVID related consequences. This is also substantiated by the comparatively higher proportion of people under these categories of the three characteristics giving favourable responses for positive and negative consequences items under the study.

Keywords

COVID-19, Pandemic, Consequences, Consequences score

Introduction

COVID-19 (Coronavirus Disease 2019) was first identified in China on November 17 2019 [1]. From there, it spread to other countries very rapidly and hence, WHO declared the disease as pandemic. The first case of COVID-19 reported in India was on 30th January 2020 [2]. The disease mainly spreads through respiratory droplets and the symptoms range from cough, throat infection, fever, body pain to the death of an individual. Older people are considered more prone to COVID-19 owing to their weak immune system [3].

The emergence of COVID-19 came as a shock to the entire world since the disease was spreading rapidly and most of the nations declared lockdown measures to contain the spread of the virus. This resulted in large scale economic disruption as most of the firms shutdown their production and business houses were closed. Many people lost their jobs and experienced difficulties in their lives due to the pandemic.

This study was carried out taking into consideration the consequences, which could have been faced by people due to the COVID-19 pandemic.

Methods and Materials

The study was conducted during the first wave of COVID-19 pandemic 2020 in India. Data was collected online through questionnaire survey using the snow ball sampling technique. The questionnaire was initially sent to some people through WhatsApp/email, with a request to forward it to more people. Accordingly, responses were obtained from 412 respondents from the States of Kerala, Karnataka, Tamil Nadu, Andhra Pradesh, Telangana, Maharashtra, Gujarat, Haryana, Rajasthan, Odisha, Bihar, West Bengal and UP in India. After removing random and incomplete data, 400 samples were considered for analysis.

The questionnaire contained 17 items related to the consequences/outcome of the pandemic. Both negative and positive consequences items were considered, which could also psychologically influence people unfavourably and favourably respectively. They were selected based on media reports, review of literature etc. The negative items relate to the direct psychological consequence of the pandemic such as mental stress and those which could indirectly affect people psychologically such as loss of income, job etc. The positive items relate to aspects such as reduced pollution and better environmental conditions due to the lock down, lock down time used for learning agriculture/fisheries etc.

The five-point continuum to the items on how much the respondents were affected due to the first wave of the pandemic were: Very much, Moderately, Less, Very less, and Not at all. These responses for the negative consequences items were scored from 1 to 5 and reverse scored for the positive items. The total score of all the items was considered as the total COVID consequences score. A higher score indicates less consequences faced by the respondent and vice versa. The level of higher consequences faced due to the pandemic in relation to the bench mark level of “No consequences” faced (as considered in this study) was calculated as follows: The total consequences score of the respondent is subtracted from the maximum possible score of 85 (which will be obtained by a respondent who has faced “No consequences” at all), divided by 85 and expressed in percentage as the level of higher consequences faced in relation to the bench mark level of “No consequences”.

The characteristics of the respondents such as sex, age, education, marital status and no. of family members were also included in the questionnaire. Data was analyzed using statistical techniques such as Factor Analysis and Odds ratio test and interpreted as proportion and scores.

Results

COVID Related Consequences Faced

Since there are negative as well as positive consequences due to the COVID-19 pandemic analyzed in this study, the terms consequences as well as outcome have been used in Table 1. 17.5% respondents were of the opinion that the COVID-19 pandemic 2020 has affected their lives very much, while, it affected 42.5% moderately. 16.5% and 10.5% mentioned that it affected them only less and very less respectively, while the pandemic did not affect 13% respondents at all (Table 1). It can be made out from Table 1 that 27.5% respondents experienced very much and 45% moderate mental stress due to the pandemic. The income of 51% respondents only were found to be affected either very much or moderately due to the pandemic, while, regarding loss of job, 34.5% report not at all affected, 12% very less and 23.5% less affected (Table 1). With respect to health care for existing/new medical problems, only 8% are very much and 25.5% moderately affected. Similarly, the respondents affected very much and moderately through increase in health problems is comparatively less than those who report less, very less and not at all affected.

Table 1: Consequences/outcome of the COVID-19 pandemic 2020.

Sl. No.

Consequence/outcome of the pandemic Respondents (%) Total (%)

Extent of consequence/outcome faced

Very much Moderately Less Very less

Not at all

1 Mental stress

27.5

45.0 13.5 5.5 8.5

100

2 Affected income

20.5

30.5 17.5 11.0 20.5

100

3 Affected due to loss of job

15.5

14.5 23.5 12.0 34.5

100

4 Affected health care for existing/new medical problems

8.0

25.5 23.5 20.0 23.0

100

5 By remaining more at home, unrest/quarrel in the family increased

4.0

12.5 22.0 15.5 46.0

100

6 Social interaction affected

42.5

31.0 12.5 6.5 7.5

100

 7 Affected freedom of movement

59.0

26.0 6.0 4.5 4.5

100

 8 Transportation affected

55.0

27.5 9.5 2.0 6.0

100

 9 Other health problems increased

2.5

17.5 24.0 20.5 35.5

100

10 Leisure/recreation activities affected

37.5

31.0 13.5 9.5 8.5

100

11 School closure increased load on parents*

32.1

28.5 15.0 10.8 13.6

100

12 Affected the capacity of old persons to support themselves**

23.3

40.7 17.4 7.6 11.0

100

13 Lock down reduced pollution and created better environmental conditions

63.5

25.5 4.5 3.5

3.0

100

14 Lock down time was used for learning agriculture/fisheries & other hobbies

100

 26.0

37.0 13.0 8.5

15.5

15 Time spent with family increased

55.0

28.0 7.0 3.0 7.0

100

 

16

Working from home helped me and my family

13.0

12.5 19.5 31.5 23.5

100

17 Family expenses reduced

13.5

11.5 21.5 42.5 11.0

100

*Among those who have children.
**Among those having old persons in their house.

Unrest/quarrel in the family has not at all increased through remaining more at home for 46% respondents, while 15.5% and 22% report very less and less increase in this respectively. 42.5% and 31% respectively reported that social interaction was affected very much and moderately due to the pandemic. 59% and 26% are of the opinion that freedom of movement has been affected very much and moderately respectively, while almost similar proportion mention that transportation was affected very much and moderately.

37.5% and 31% respondents report that their leisure/recreation activities were affected very much and moderately respectively. A total of 64% respondents report that the pandemic affected the capability of old persons to support themselves either very much or moderately. Work from home during the pandemic period was less and very less helpful for 51% respondents, while it did not help 23.5% respondents at all.

A total of 64% respondents reports only less or very less reduction in family expenses during the pandemic period.

63.5% and 25.5% respondents are of the opinion that the pandemic induced lock down very much and moderately reduced pollution and created better environmental conditions respectively. Similarly, the lock down time was used for learning agriculture/fisheries & other hobbies by a total of 63% respondents very much and moderately. Time spent with their families increased very much during the pandemic period for 55% and moderately for 28% respondents, even though the level of social interaction with other people was restricted very much for 42.5% and moderately for 31% respondents.

COVID Consequences Score

Table 2 shows the total COVID consequences score of the respondents categorised based on the quartile method. A high score indicates that the respondents have faced low consequences and vice versa for a low score. Majority (44.5%) of the respondents in the study have faced medium COVID related consequences, while 27.5% faced low consequences only. It may be made out from Table 3 that in the case of 77.5% respondents, more consequences faced (in relation to the condition of “No consequences faced”) is in the range of 57.6% to 35.3%. More consequences faced is in the lowest range of 34.1 to 14.1% only for 13.7% respondents.

Table 2: Categories of total COVID consequences score.

Total consequences score category*

Mean score Minimum score Maximum score

Respondents (%)

High**

57.14

52 73

27.5

Low***

36.17

16 41

28.0

Medium

46.26

42 51

44.5

Total

46.43

16 73

100

*Based on quartile method.
**Low consequences faced.
***High consequences faced.

Table 3: Range of total COVID consequences score.

Range of total consequences score

Range (%) of more consequences faceda

Respondents (%)

16-35

81.2-58.8

8.8

36-55

57.6-35.3

77.5

56-73

34.1-14.1

13.7

Total

100

aIn relation to the condition of “No consequences faced”.
Lower the score, higher the consequences faced.

Characteristics Contributing to the Consequences Score

Factor analysis was carried out to determine the major characteristics of the respondents contributing to the total COVID consequences score. The results are presented in Table 4, which shows that the first four factors show significant eigen value (>1) and explain 69.92% of the variability in the total score of the respondents. Among the characteristics, age, education, and no. of family members contribute significantly (factor loading>0.50) to the factor components observed in the total consequences score.

Table 4: Factor analysis of total COVID consequences score.

Characteristics

Factor loading

Factor

1

2 3

4

Age

0.77

-0.02 0.64

0.00

Sex

0.29

0.10 0.25

-0.34

Education

-0.31

0.90 0.30

0.00

Marital status

0.37

0.02 0.19

0.55

No. of family members

-0.69

-0.44 0.58

0.00

Family members less10 years of age

-0.32

-0.10 0.11

0.30

Marital status

-0.02

-0.10 0.44

-0.07

Income

-0.03

0.39 0.21

0.15

Initial Eigen values

1.78

1.44 1.29

1.06

Variance (%)

22.36

18.11 16.12

13.32

Cumulative %

22.36

40.47 56.60

69.92

Chances to Obtain High Total COVID Consequences Score for People with Different Age, Education and No. of Family Members

Table 5 shows the results of the statistical test of odds ratio with respect to high total consequences score (less consequences faced) with respect to age, education and no. of family members, which showed high factor loading (Table 4). It can be made out from Table 5 that respondents with more than 4 family members have 0.37 times more chances of obtaining high score (indicting less consequences) than those with less than 4 family members. Similarly, respondents aged more than 40 years have 0.79 times more chances of obtaining high score (indicting less consequences) than those aged less than 40. However, PhD holders have 0.33 times less chances of obtaining high score (indicting less consequences) than those who have PG and Degree.

Table 5: Odds ratios of personal characteristics on total COVID consequences score.

Characteristic

Category

Odds ratio*

Age

>40 vs.<40

1.79

No. of family members

>4 vs.<4

1.37

Education

PhD vs PG and Degree

0.67

*Indicating the chances of respondents to have a high total score (less consequences faced).

Considering 13.7% respondents shown in Table 3 who have the highest range of total score of 56 to 73 (which implies that only 34.1% to 14.1% more consequences have been faced by them than the condition of “No consequences faced”), 63.6% of these respondents are found to have a total score of 60 and above. Total consequence score of 60 and above implies that the higher consequences faced by them in relation to the condition of “No consequences faced” is 29.4% and less only.

Hence, based on the results of factor analysis (Table 4) and odds ratio (Table 5), the proportion of respondents under different categories of age, education and no. of family members (the characteristics considered in working out the odds ratio) was worked out for those getting a total consequence score of 60 and above. The results are shown in Table 6.

Table 6: Age, Number of family and education of respondents having high total COVID consequences score.

Respondents (%) with total consequences score of 60 and above

Age No. of family members

Education

Up to 40

>40

Up to 4 >4 PhD

PG and Degree

26.0

74.0

40.7 59.3 26.0

74.0

The maximum total score of respondents in the study was 73.

It can be made out from Table 6 that while 74% respondents aged more than 40 years have total consequences score of 60 and above, only 26% below 40 years of age have this score. This could be the reason for the odds ratio of 1.79 for age (Table 5), which implies that respondents aged more than 40 years have 79% more chance of obtaining high score (less consequences) than those aged less than 40.

Similarly, while 59.3% of respondents with more than 4 family members get a total consequence score of of 60 and above, the figure is only 40.7% for those with less than 4 members (Table 6). This could be why the odds ratio of 1.37 is there for no. of family members (Table 5), indicating that respondents with more than 4 family members have 37% more chance of obtaining high score (less consequences) than those with less than 4 family members.

However, with regard to education, while 74% respondents with PG and Degree have total consequences score of 60 and above, only 26% with PhD are having this score. The odds ratio was 0.67 for education (Table 5), which means that PhD holders have 33% less chance of obtaining high score (less consequences) than those with PG and Degree qualifications.

For better interpretation of the influence of age, education and no. of family members (family size) on the total COVID consequences score (whose results were observed in the odds ratio test), the variation in proportion of responses to different consequences items were worked out for these characteristics. Only perceptible differences in the responses to the consequences items between various categories of the characteristics have been included in the concerned tables which follow.

Age wise responses to different consequences items are shown in Table 7. With respect to the negative consequence item, namely, income affected due to the COVID-19 pandemic, while 31.7% respondents up to 40 years of were very much affected, only 10.5% of those with more than 40 years of age report in this manner. Further, 27% of those aged more than 40 reports that income was not at all affected due to the occurrence of the pandemic, when compared to only 12.3% of those less than 40 years of age (Table 7). While 19% of respondents up to the age of 40 were affected very much due to loss of job, the figure for more than 40 age respondents is only 6%. 19.5% of respondents with age more than 40 were less affected due to job loss, while only 15.5% of people up to 40 years of age report in this manner (Table 7).

Table 7: Age wise responses to consequences items.

Sl. No.

Consequence item Age group Respondents (%)
Very much Moderately Less Very less

Not at all

 1 Income affected

Up to 40

31.7 NA* NA NA

12.3

>40

10.5 NA NA NA

27.0

 2 Job loss

Up to 40

19.0 NA 15.5 NA

NA

>40

 6.0 NA 19.5 NA

NA

 3 Time spent with the family increased

Up to 40

NA NA 7.8 NA

7.2

>40

NA NA 4.8 NA

5.4

 4 Due to lockdown, quarrel/unrest in the family increased

Up to 40

6.1 17.8 NA NA

34.0

>40

2.5 7.6 NA NA

51.2

 5 Affected freedom of movement

Up to 40

61.1 NA NA 3.9

3.9

>40

56.7 NA NA 5.4

7.4

 6 Transportation affected

Up to 40

62.8 NA 8.3 0.6

NA

>40

48.0 NA 10.4 3.7

NA

 7 Stress level including fear of virus infection increased

Up to 40

34.4 NA NA NA

7.8

>40

18.8 NA NA NA

12.8

 8 Other diseases/health problems increased

Up to 40

NA 21.7 NA 18.3

26.7

>40

NA 14.4 NA 20.9

37.2

 9 Health care for existing/new medical problems increased

Up to 40

11.1 NA 18.9 15.7

NA

>40

 6.0 NA 21.3 18.4

NA

 10 Leisure/recreation activities affected

Up to 40

37.8 NA NA 7.2

11.6

>40

34.2 NA NA 9.5

13.8

 11 School closure increased pressure/load in children and parents

Up to 40

33.9 25.0 7.8 6.1

NA

>40

11.0 14.9 12.6 12.6

NA

 12 Affected the capacity of older people to support themselves

Up to 40

26.2 NA 14.4 3.3

7.2

>40

13.8 NA 16.3 9.1

12.9

 13 Lockdown time was used in learning/doing agriculture/fisheries etc.

Up to 40

NA 31.1 16.2 NA

NA

>40

NA 41.6 10.1 NA

NA

*Data not shown since perceptible difference was not observed in these responses for the consequences items

Now, considering a positive consequence item -time spent with family increased during the pandemic period, Table 7 shows that while a higher proportion (7.8%) respondents under the age group of more than 40 report as less time spent with the family, only 4.8% respondents with more than 40 age report so. Further, while 7.2% of up to 40 age report as not all spent time with the family, only 5.4% of people aged more than 40 report in this manner.

Similarly, considering the other consequences items shown in Table 7, it can be inferred that a comparatively lower proportion of respondents above the age of 40 report affected very much/moderately for the negative consequences items than those with up to 40 years of age, while a higher proportion of respondents above the age of 40 report affected less/very less/not at all for the negative consequences items, when compared to the respondents aged up to 40 years. Similarly, with regard to the positive consequences items shown in Table 7, a comparatively higher proportion of respondents above the age of 40 report as experiencing very much/moderately for the positive consequences items than those with up to 40 years of age, while a lower proportion of respondents above the age of 40 report as less/very less/not at all for the positive items, when compared to respondents aged up to 40 years.

These trends indicate that people with more than 40 years of age have faced comparatively less consequences than those aged less than 40 years. This would also help to substantiate the results of the odds ratio of 1.79 for age of the respondents (Table 5), which implies that respondents in the study who are aged more than 40 years have 79% more chance of obtaining a high score/facing less consequences) than those aged less than 40.

As in the case of age, it can be inferred from the data presented in Table 8 that a comparatively lower proportion of respondents with PG and Degree qualification report affected very much/moderately for the negative consequences items than those having PhD, while a higher proportion of respondents with PG and Degree report as affected less/very less/not at all for the negative consequences items, when compared to those having PhD. Similarly, with regard to the positive consequences items, a comparatively higher proportion of respondents with PG and Degree report as experiencing very much/moderately for the positive consequences items than those with PhD, and a lower proportion of PG and Degree respondents report less/very less/not at all for the positive items, when compared to respondents having PhD qualification.

Table 8: Education wise responses to consequences items.

Sl. No.

Consequence item Education Respondents (%) reporting
Very much Moderately Less Very less

Not at all

1 Income affected PG and Degree

NA

28.0 NA* NA

21.4

PhD

NA

36.2 NA NA

16.2

2 Loss of job PG and Degree

NA

NA 19.4 NA

28.2

PhD

NA

NA 15.0 NA

23.7

4 Due to lockdown, quarrel/unrest in the family increased PG and Degree

NA

12.9 NA 13.6

44.4

PhD

NA

15.0 NA 10.0

32.5

5 Social interaction and cohesion affected PG and Degree

NA

27.8 12.3 7.3

NA

PhD

NA

40.0 8.8 2.5

NA

6 Affected freedom of movement PG and Degree

57.0

NA NA NA

5.4

PhD

60.0

NA NA NA

2.5

7 Transportation affected

 

PG and Degree

51.0

NA 9.7 NA

7.4

PhD

 

62.4

NA 8.8 NA

3.8

8 Stress level including fear of virus infection increased PG and Degree

NA

43.4 14.4 6.0

10.0

PhD

NA

57.4 8.8 3.8

7.5

9 Other diseases/health problems increased PG and Degree

NA

15.7 NA 33.7

4.4

PhD

NA

25.0 NA 27.5

Nil

10 Health care for existing/new medical problems increased PG and Degree

NA

15.7 NA 23.0

33.7

PhD

NA

25.0 NA 11.3

27.5

11 School closure increased pressure/load in children and parents PG and Degree

20.2

NA NA 8.7

NA

PhD

25.0

NA NA 5.0

NA

12 Affected the capacity of older people to support themselves PG and Degree

NA

35.1 NA 11.0

NA

PhD

NA

37.5 NA 7.5

NA

*Data not shown since perceptible difference was not observed in these responses for the consequences items

These findings indicate that people with PG and Degree qualifications have faced comparatively less consequences than those having PhD, which would also support the result of odds ratio of 0.67 for Education (Table 5), which implies that PhD holders have 33% less chance of obtaining high score/facing less consequences than those with PG and Degree qualifications.

It can be made out from Table 9 that comparatively less proportion of respondents having more than 4 family members report affected very much/moderately for the negative consequences items than those with a family size of 4 members, while a higher proportion of respondents with family size of more than 4 members report affected less/very less/not at all for the negative consequences items than the respondents with a family size of 4 members. Similarly, for the positive consequences items, comparatively high proportion of respondents with more than 4 family members report experiencing the positive consequences items very much/moderately than those with only 4 members, and a lesser proportion with more than 4 family members report less/very less/not at all for the positive items, when compared to respondents with a family size of 4.

Table 9: Family size wise responses to consequences items.

Sl. No.

Consequence item No. of family members Respondents (%) reporting
Very much Moderately Less Very less

Not at all

1 Work from home helped me/my family

Up to 4

7.9 30.9 NA NA NA
>4 11.1 45.3 NA NA

NA

2 Social interaction and cohesion affected

Up to 4

NA 43.2 9.6 5.3

4.7

>4

NA 18.7 17.9 9.3

13.4

3 Affected freedom of movement

Up to 4

NA 38.0 6.1 2.1

1.2

>4

NA 19.3 9.5 10.6

8.4

4 Affected the capacity of older people to support themselves

Up to 4

NA 36.6 14.3 4.7

NA

>4

NA 25.6 22.6 14.0

NA

5 Lockdown reduced pollution and created better environmental conditions

Up to 4

52.2 NA 11.0 NA

NA

>4

74.9 NA  1.2 NA

NA

6 Lockdown time was used in learning/doing agriculture/fisheries etc.

Up to 4

24.9 NA NA 14.6

11.5

>4

38.4 NA NA  4.5

5.9

*Data not shown since perceptible difference was not observed in these responses for the consequences items

Similar to age and education, these results substantiate the odds ratio of 1.37 for the characteristic, namely, no. of family members (family size), which indicates 37% more chance for respondents with a family size of more than 4 members to get a high COVID consequences score/face less consequence than those having a family size of less than 4.

Discussion

The study shows that a high proportion of respondents representing various States of India experienced very much and moderate mental stress due to the pandemic. WHO has warned of a “massive increase in mental health conditions” arising from the pandemic. Mental health experts in Mumbai have observed an increase in feelings of anger, frustration and helplessness. [4]. However, in a study conducted in Kerala State of India by WEDO (NGO), majority of the respondents did not experience high level of negative feelings/mental state on the COVID pandemic, while most of them experienced the positive feelings well [5].

A survey found that 77% of economically active adults in India had lost income due to the pandemic (https://www.hindustantimes.com/india-news/77-indian-adults-lost-income-due-to-covid-19-pandemic-survey/story-QjCVwkt4xNmJwcHw4I5wMP.html-retrieved 22 Aug 2021). According to WHO, the COVID-19 pandemic has decimated jobs and many are without the means to earn an income and the access to quality health care during the pandemic induced lockdown (Source: Impact of COVID-19 on people’s livelihoods, their health and our food systems-Joint statement by ILO, FAO, IFAD and WHO. October 2020. https://www.who.int/news/item/13-10-2020-impact-of-covid-19-on-people’s-livelihoods-their-health-and-our-food-systems-retrieved 22nd August 2021)). Health is defined by WHO as the “state of complete physical, mental and social well-being and not merely the absence of disease or infirmity” (World Health Organization (WHO). Naming the coronavirus disease (COVID19) and the virus that causes it. https://www.who.int/emergencies/diseases/novelcoronavirus-2019/technical-guidance/naming-the-coronavirus-disease-(covid2019)-and-the-virus-that-causes-it. – retrieved 1st November 2021). However, in the present study, income of about 50% of the respondents only were found to be affected either very much or moderately due to the pandemic, while 70% respondents mention as not at all affected, very less and less affected with respect to job. Health care for existing/new medical problems are very much and moderately affected on account of the pandemic for some respondents only. Similarly, those who are affected very much and moderately through increase in health problems is comparatively less than the total proportion reporting less, very less and not at all affected.

Not only is the infection with COVID-19 disease a risk, but people are limiting their social interactions with others, working from home, and avoiding unnecessary gatherings. In this study also, social interaction was affected very much and moderately due to the pandemic for a very high proportion of respondents.

While overcoming the COVID-19 pandemic relies on an efficient strategy that involves the whole population, the elderly people are disproportionately affected by this disease [6]. In this study also a good proportion mention that the pandemic affected the capability of old persons to support themselves either very much or moderately.

The advantages of working from home include reduced commuting time, avoiding office politics, using less office space, increased motivation, improved gender diversity (e.g. women and careers), healthier workforces with less absenteeism and turnover, higher talent retention, job satisfaction, and better productivity [7,8]. However, the present study has shown that work from home during the pandemic period was not at all, very less and less helpful for a very high proportion of people.

Slowdown in spending by Indian households is reported to have saved additional $200 billion during Covid pandemic and lockdowns. (https://economictimes.indiatimes.com/news/economy/indicators/indians-saved-additional-200-billion-during-covid-pandemic-and-lockdowns/articleshow/80386426.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst- retrieved 24th August 2021). However, in the present study, high proportion of respondents representing various States of India reported only less or very less reduction in family expenses during the pandemic period.

The study has also shown some positive outcomes during the pandemic period. Very high proportion of respondents report that the COVID 19 induced lock down reduced pollution and created better environmental conditions very much and moderately. Similarly, the lock down time was used for learning agriculture/fisheries and other hobbies very much and moderately by a high proportion of respondents. Even though the level of social interaction outside the family was significantly restricted, time spent with their families increased very much and moderately during the pandemic period for many respondents. Unlike the past, the onset of the COVID pandemic and the resultant lockdown has given families across India and the world a new lease of familial bonding that was otherwise hard to come by. For the first time in a long time, many parents and kids and even grandparents are all under the same roof round-the-clock. This enforced togetherness can deepen relationships for years to come. According to Brad Wilcox, a professor of sociology and director of the National Marriage Project at the University of Virginia, people and families when faced with a global crisis, and especially one of this scale, tend to respond by orienting themselves in a less self-centred way and in a more family-centric way (https://timesofindia.indiatimes.com/life-style/spotlight/how-the-lockdown-is-cementing-relationships-and-bringing-families-together/articleshow/75731732.cms- retrieved 23rd August 2021).

The results reveal that majority of the respondents have faced medium to low COVID related consequences only. Further, people aged more than 40 years, with PG and Degree qualifications, and having more than 4 family members have faced less COVID related consequences only. This is substantiated by the comparatively higher proportion of people under these categories of age, education and no. of family members giving favourable responses for positive and negative consequences items. These findings also support the odds ratio values observed for these categories of the characteristics, which indicate the chances for people falling under the particular categories to face less COVID consequences.

To conclude, majority of the respondents under the study have faced medium level of COVID-19 related consequences, while some of them faced low consequences only. Negative consequences include mental stress, income/job loss, less social interaction, increase in health problems, unrest or quarrel in the family, social interaction/transportation/recreation/capability of old people to support themselves/health care for medical problems being affected, work from home not helpful, and less reduction in family expenses during the pandemic. Positive consequences of the pandemic such as reduced pollution and better environmental conditions due to lock down, lock down time used for learning agriculture/fisheries, and increase in time spent with family are also observed in the study. Age, education, and no. of family members of the respondents explain 69.9% of the variability in their total consequences score. People aged more than 40 years, those with PG and Degree qualifications, and people having more than 4 family members are found to have faced less consequences only. This is also substantiated by the comparatively higher proportion of people under these categories of age, education and no. of family members giving favourable responses for positive and negative consequences items under the study.

It would be worthwhile if studies on the consequences of the COVID-19 pandemic occurring during different periods are carried out in various parts of the affected countries in order to facilitate the health and other field level workers to introduce location specific measures/strategies to address the problems faced by people. The development of useful information through such studies appears to be essential in the days to come for the policy makers also, keeping in mind the fact that the pandemic is continuing in time, space and severity in different parts of the world even now.

References

  1. Balkhi F, Nasir A, Zehra A, Riaz R (2020) Psychological and behavioral response to the coronavirus (COVID-19) pandemic. Cureus. 12: 5.[crossref]
  2. Annamuthu P, Shenbagavadivu, T, Arthi S (2020) A study on the perception and precautionary measures taken by the general public amidst COVID-19. Int J Modern Trends Sci Technol 6: 169-74.
  3. Mikaberidze A (2020) Letter To the Editor: “Letter to the Editor.” International Journal of Phytoremediation 20: 135-136.
  4. Fuad Bakioğlu, Ozan Korkmaz, Hülya Ercan (2020) Fear of COVID-19 and Positivity: Mediating Role of Intolerance of Uncertainty,Depression, Anxiety, and Stress. Int J Ment Health Addict. 28: 1-14.[crossref]
  5. Madhava Chandran K, Naveena K, Valsan T, Sreevallabhan S (2021). Analysis of the Mental State of People on COVID-19 Pandemic. International Journal of Indian Psychology 9: 839-845.
  6. Daoust J-F (2020) Elderly people and responses to COVID-19 in 27 Countries. [crossref]
  7. Mello JA (2007)Managing Telework Programs Effectively. Employee Responsibilities and Rights Journal 19: 247-261.
  8. Robertson MM, Maynard WS, McDevitt JR (2003) Telecommuting: Managing the Safety of Workers in Home Office Environments. Professional Safety 48: 30-36.