Impact of the COVID-19 Pandemic on the Wellbeing of Tribal Women of Reproductive Age in a Rural Remote Region: An Observational Study

Research Article

Impact of the COVID-19 Pandemic on the Wellbeing of Tribal Women of Reproductive Age in a Rural Remote Region: An Observational Study

  • Chhabra S 1*
  • Kumar N 2

1Senior Obstetrician - Gynaecologist, Tapanbhai Mukeshbhai Patel Memorial Hospital and Research Center Shirpur (Dhule) Shri Vile Parle Kelavani Mandal, Mumbai, Maharashtra, India.

2Associate Professor, Obstetrics and Gynecology, All India Institute of Medical Sciences, Bibinagar-508126, Hyderabad Metropolitan Region, Telangana, India.

*Corresponding Author: Chhabra S, Senior Obstetrician - Gynaecologist, Tapanbhai Mukeshbhai Patel Memorial Hospital and Research Center Shirpur (Dhule) Shri Vile Parle Kelavani Mandal, Mumbai, Maharashtra, India.

Citation: Chhabra S, Kumar N. (2024). Impact of the COVID-19 Pandemic on the Wellbeing of Tribal Women of Reproductive Age in a Rural Remote Region: An Observational Study. Journal of Women Health Care and Gynecology, BioRes Scientia Publishers. 3(6):1-8. DOI: 10.59657/2993-0871.brs.24.049

Copyright: © 2024 Chhabra S, this is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Received: June 03, 2024 | Accepted: June 20, 2024 | Published: June 26, 2024

Abstract

Background COVID-19 pandemic caused unprecedented impact on society globally. Present study was conducted to explore hardships experienced by rural women of reproductive age in remote area. Methodology Community-based cross-sectional observational study included 2500 randomly selected tribal women between ≥20 to ≤49 years, residing in 140 villages and consenting to participate. Face-to-face interviews of participants were conducted for 15-30 minutes using semi-structured questionnaire regarding sufferings during COVID-19 pandemic. Results of 2500 women interviewed, majority (57.7%) were 20-29 years old, with lower education (48.1%), agriculture laborer (45.4%), of lower economic class (48.8%). Of all participants 24.4% reported change in meals, 18.2% change in work and working environment, 52.1% change in health care. Of total, 40.8% reported physical violence (PV), 52.1% reported increased PV during pandemic, majority (66.7%) by husbands, 39.4% suffered sexual violence (SV), 38.5% reported increased SV during pandemic. Modes of PV were mostly slapping or hitting or kicking. Of all, who suffered PV, and SV, majority informed to their family members, but only 12.1% and 7.4% of those who suffered PV and SV respectively informed police and 66.1% and 41.5% suffering PV and SV sought healthcare. Socio-demographic factors like age, education, economic class, occupation had significant relationship with sufferings of women during pandemic. Conclusion: Pandemic had significant impact on rural women’s lives, 40.8% and 39.4% of women respectively were found to have suffered PV and SV at home during COVID-19 pandemic. It is therefore necessary to generate awareness, formulate laws and policies for protection of women during such pandemics.


Keywords: COVID-19; pandemic; physical violence; sexual violence; rural women

Introduction: Background

COVID-19 pandemic caused an unprecedented impact on society across the globe [1]. The pandemic has affected people around the world with increased social, economic, physiological, and psychological hardships for everyone [2]. It has intensified human sufferings, weakened the economy, disrupted the lives of billions worldwide, with a profound impact on health, economic, environmental, and social aspects of life [3]. The COVID-19 pandemic has placed tremendous pressure on health systems across the globe, not only because of its direct effects but indirectly also [4]. Health inequalities have always existed in different regions, and the pandemic has further exacerbated these disparities, resulting in varying levels of illnesses, their severity and mortality rates [5, 6]. National responses to the pandemic have varied between countries and even among provinces within a country. These differences depended on various factors, including the COVID-19 burden, public awareness, available resources, infrastructure, and human resources [7, 8]. Rural populations in developing countries live with limited resources, and the pandemic has severely impacted their lives, leading to extreme hardships and struggles for survival, particularly for women. The lack of resources has driven them into financial crises on both personal and familial levels. Work suspensions due to lockdowns aimed at preventing the spread of coronavirus contributed to a severe financial crisis specially to rural communities [9, 10]. 

Objective

A community-based study was done to explore the hardships experienced by rural women of reproductive age during the COVID-19 pandemic in a remote area.

Material and methods

Study design: Observational cross-sectional study

Study setting and duration: The study was conducted over a period of one year in a total of 140 tribal villages in remote, forestry, and hilly region. These villages were around the village with the health facility, the study center.

Inclusion criteria: Randomly 15 women, between ≥20 to ≤49 years of age selected from each village and willing to undergo a personal interview were enrolled as study participants, considering some villages were small and some large.

Exclusion criteria: Women <20>49 years, not willing to be a part of the study were excluded. 

Sample size: Calculated sample size was 2500 with 95% confidence and 2

Results

Of all the women interviewed, majority (57.7%) were of 20-29 years of age, educated up to primary level (48.1%), agriculture laborer by occupation (45.4%), belonging to lower economic class (48.8%) and had one or two births (57.8%), and they reported that their lives significantly changed during COVID-19 pandemic. Of these 2500 women, 609 (24.4%) reported change in their meals due to lockdown, loss of family members employment, problems in agriculture, and poverty. 456(18.2%) reported change in their work and working environment due to lockdown and loss of jobs, 1303(52.1%) reported change in health care as many were not able to reach hospitals for various ailments due to lockdown. There was lack of health facilities with financial constraints also. The remaining 132(5.3%) women reported other changes like mental health, fear of infection, insecurity, change of homes due to shifting to other places when jobs were lost, school drop-outs of children, etc.

Of 2500 women, a total of 1019 (40.8%) reported physical violence (PV) at their homes during the pandemic, of which 531(52.1%) reported increase in PV during pandemic compared to pre-pandemic period. Of these 1019 women, 680 (66.7%) reported PV by their husbands, 221(21.7%) by father- and brother-in laws, 100 (9.8%) by mother- and sister-in laws and remaining 18(1.8%) by uncles, aunts, cousins. Table 2 depicts the relationship between the various socio-demographic features of women and PV at home by family members (Table 2). When interviewed about the frequency and mode of physical violence at home, of 1019 women, 885 (86.8%) reported occasional episodes of PV whereas 134 (13.2%) reported regular PV at home. The majority (86.1%) reported slapping, hitting by hands or kicking as the most common modes of PV followed by hitting with bar rods or burning (12.5%) and the remining 1.5% reported other means like hitting with brooms, foot wares, utensils, etc. The majority of these sufferers belonged to 20-29 years of age, having low education, were agricultural laborers by occupation, and belonged to low economic class. Table 3 depicts the relationship of socio-demographic features of women with the frequency and mode of PV suffered at home (Table 3). Of all the women who suffered PV, 878(86.2%) informed someone, including family members (85.6%), police (12.2%), and others like neighbors, friends, and distant relatives (2.3%) (Table 4). Of these 1019 women, only 580 (66.1%) had to seek healthcare with 74.1% of them from Subcentres (SC) or Primary Health Centres (PHC), 23.3% from Sub-district hospital (SDH)/District hospital (DH), and remaining 2.6% from private hospitals or dispensaries. The relationship of the action taken and health care sought for PV suffered at home and demographic factors is shown in table 4 (Table 4)

Table 1: Changes in Every Day Life During COVID-19 Pandemic

VariablesTotal **Mode of change      
Age (Years) Meals%Work%Health care%Others%
≥20 - ≤29144226118.128119.582156.9795.5
≥30 - ≤396059916.41212034156.4447.3
≥40 - ≤49453249555411.914131.192
Total250060924.445618.2130352.11325.3
Education
Illiterate71713418.713919.440556.5395.4
Primary120331626.321918.260450.2645.3
Secondary / Higher Secondary43069169121.224156296.7
Graduate150906074.75335.300
Total250060924.445618.2130352.11325.3
Profession
Home Maker72025435.3517.139154.3588.1
Agriculture Laborer113630626.9948.364857746.5
Casual Laborer *5646912.223641.825945.900
Shop keeper80007593.856.300
Total250060924.445618.2130352.11325.3
Economic Status
Upper Class751925.334516822.7
Upper Middle Class1052221109.57167.621.9
Middle Class4055413.311127.421152.1297.2
Lower Middle Class695146211462134549.6588.3
Lower Class122036830.218615.262551.2413.4
Total250060924.445618.2130352.11325.3
Parity
P02054622.43617.69144.43215.6
P1 - P2144532222.33042176152.7584
> P385024128.411613.645153.1424.9
Total250060924.445618.2130352.11325.3

*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace, **Everyone said their lives got affected, P: Previous viable births.

Table 2: Physical Violence at Home During COVID-19

VariablesTotalStarted IncreasedIf, yes       
Age (Years)Yes%Yes%Husband%Father-in-law / Brother-in-law%Mother-in-law/ Sister-in-law%Others%
≥20 - ≤29144261942.931150.244371.510116.36510.5101.6
≥30 - ≤3960526243.314555.313551.59536.3259.572.7
≥40 - ≤4945313830.57554.310273.92518.1107.210.7
Total2500101940.853134.468066.722121.71009.8181.8
Education
Illiterate71721029.317583.310650.56229.53516.773.3
Primary120352543.628153.539274.79317.7326.181.5
Secondary / Higher Secondary43018843.77539.98947.36534.63116.531.6
Graduate1509664009396.91122.100
Total2500101940.853152.168066.722121.71009.8181.8
Profession
Home Maker72027738.51194316659.96523.53713.493.2
Agriculture Laborer11364884329560.534270.110120.7387.871.4
Casual Laborer*56421938.811050.213762.55525.12511.420.9
Shop keeper803543.872035100000000
Total2500101940.853152.168066.722121.71009.8181.8
Economic Status
Upper Class752533.30025100000000
Upper Middle Class1054038.1512.540100000000
Middle Class40518846.44523.914677.62513.315821.1
Lower Middle Class6952854110035.117461.18529.820762.1
Lower Class122048139.438179.229561.311123.16513.5102.1
Total2500101940.853152.168066.722121.71009.8181.8
Parity
P02059043.945505257.8273088.933.3
P1- P2144558940.831152.839466.912521.26010.2101.7
> P38503404017551.523468.86920.3329.451.5
Total250010194153152.168066.722121.71009.8181.8

*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace. P: Previous viable births.

Table 3: Physical Violence Frequency and Mode at Home

VariablesTotalFrequency of violence Mode of violence    
Age (Years)Once / occasional%Regular%Slap / hitting / kicking%Bar / rod / burns%Others%
≥20 - ≤2961953987.18012.953386.17712.491.5
≥30 - ≤3926221782.84517.221381.34316.462.3
≥40 - ≤4913812993.596.513194.975.100
Total101988586.813413.287786.112712.5151.5
Education
Illiterate210170814019168803818.141.9
Primary52546087.66512.445486.5631281.5
Secondary / Higher Secondary18815984.62915.415984.62613.831.6
Graduate969610000961000000
Total101988586.813413.287786.112712.5151.5
Profession
Home Maker27721878.75921.321477.35620.272.5
Agriculture Laborer48841384.67515.441184.27114.561.2
Casual Laborer *2192191000021799.10020.9
Shop keeper353510000351000000
Total101988586.813413.287786.112712.5151.5
Economic Status
Upper Class2523922824961400
Upper Middle Class403895253997.512.500
Middle Class18815884301616085.12513.331.6
Lower Middle Class28522679.35920.722277.95920.741.4
Lower Class48144091.5418.543289.8418.581.7
Total101988586.813413.287786.112712.5151.5
Parity
P0905864.43235.65864.43033.322.2
P1- P258953090591052489579.781.4
> P334029787.44312.629586.84011.851.5
Total101988586.813413.287786.112712.5151.5

*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace, P: Previous viable births.

Table 4: Action Taken for Physical Violence

VariableTotalYes%Person    Yes%Health Care Sought and Place 
Age In Years  Family member%Police%Others%  *SC /PHC%**SDH / DH%Others%
≥20 - ≤2961953486.345685.46712.5112.144082.435179.88018.292
≥30 - ≤3926221481.717983.62712.683.79544.44951.64042.166.3
≥40 - ≤4913813094.211790129.210.84534.63066.71533.300
Total101987886.275285.610612.1202.358066.143074.113523.3152.6
Education
Illiterate21016980.512473.43721.984.7105.9101000000
Primary52545486.541190.5347.59238885.525164.712532.2123.1
Secondary / Higher Secondary18815984.612377.43320.831.989567685.41011.233.4
Graduate96961009497.922.1009396.9931000000
Total101987886.275285.610612.1202.358066.143074.113523.3152.6
Profession
Home Maker27721577.616677.23918.1104.714567.49766.94128.374.8
Agriculture Labourer48841184.236388.3409.781.930574.223978.46019.762
Casual Laborer*21921799.118886.62712.420.910046.17373252522
Shop keeper35351003510000003085.7217093000
Total101987886.275285.610612.1202.358066.143074.113523.3152.6
Economic Status
Upper Class25249624100000024100241000000
Upper Middle Class403997.53910000003589.7351000000
Middle Class18816085.114188.11710.621.314691.314095.932.132.1
Lower Middle Class28522378.219487229.973.119085.213168.95528.942.1
Lower Class48143289.835481.96715.5112.518542.810054.17741.684.3
Total101987886.275285.610612.1202.358066.143074.113523.3152.6
Parity
P0905864.44577.61017.235.25289.73567.31528.823.8
P1- P 258952589.145286.16211.8112.133563.823269.39528.482.4
> P334029586.825586.43411.56219365.416384.5251352.6
Total101987886.275285.610612.1202.358066.143074.113523.3152.6

*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace *SC – Subcentre; PHC – Primary health care; **SDH – Sub-district hospital; DH –District hospital, P: Previous viable births.

Furthermore, of the total of 2500 women interviewed, 985(39.4%) reported sexual violence (SV) at their homes during the pandemic with 379 (38.5%) reporting increase in SV compared to pre-pandemic period. Of these 985 women, 796 (80.8%) reported SV by their husbands, 120 (12.2%) by father- and brother-in laws, and remaining 69 (7.0%) by uncles, cousins, etc. Of these 985 women, 922(93.6%) reported occasional attempts of SV whereas 63 (6.4%) reported regular attempts by family members. Table 5 depicts the relationship between the socio-demographic features of women and SV at home (Table 5). Of all the women who suffered SV, 742(75.3%) informed someone, including family members (90.6%), police (7.4%), and others like neighbors, friends, and distant relatives (2.0%) (Table 6). Of these 985 women, 409(41.5%) sought healthcare-related help too with 92.7% from SC or PHC, 5.6% from SD/DH, and remaining 1.7% from private hospitals or dispensaries. The relationship of the action taken and health care sought for SV suffered at home and demographic factors is shown in table 6 (Table 6).

Table 5: Sexual Violence at Home

VariableTotalYes%Person    Yes%Health Care Sought and Place  
Age In Years  Family member%Police%Others%  *SC /PHC%**SDH / DH%Others%
≥20 - ≤2961953486.345685.46712.5112.144082.435179.88018.292
≥30 - ≤3926221481.717983.62712.683.79544.44951.64042.166.3
≥40 - ≤4913813094.211790129.210.84534.63066.71533.300
Total101987886.275285.610612.1202.358066.143074.113523.3152.6
Education
Illiterate21016980.512473.43721.984.7105.9101000000
Primary52545486.541190.5347.59238885.525164.712532.2123.1
Secondary / Higher Secondary18815984.612377.43320.831.989567685.41011.233.4
Graduate96961009497.922.1009396.9931000000
Total101987886.275285.610612.1202.358066.143074.113523.3152.6
Profession
Home Maker27721577.616677.23918.1104.714567.49766.94128.374.8
Agriculture Labourer48841184.236388.3409.781.930574.223978.46019.762
Casual Laborer*21921799.118886.62712.420.910046.17373252522
Shop keeper35351003510000003085.7217093000
Total101987886.275285.610612.1202.358066.143074.113523.3152.6
Economic Status
Upper Class25249624100000024100241000000
Upper Middle Class403997.53910000003589.7351000000
Middle Class18816085.114188.11710.621.314691.314095.932.132.1
Lower Middle Class28522378.219487229.973.119085.213168.95528.942.1
Lower Class48143289.835481.96715.5112.518542.810054.17741.684.3
Total101987886.275285.610612.1202.358066.143074.113523.3152.6
Parity
P0905864.44577.61017.235.25289.73567.31528.823.8
P1- P 258952589.145286.16211.8112.133563.823269.39528.482.4
> P334029586.825586.43411.56219365.416384.5251352.6
Total101987886.275285.610612.1202.358066.143074.113523.3152.6

*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace, P: Previous viable births

Table 6:Action Taken for Sexual Violence

VariableTotalYes%Person    Yes%Health Care Sought and Place  
Age (Years)  Family member%Police%Others%  *SC /PHC%**SDH / DH%Others%
≥20 - ≤2960550984.146491.9377.381.626143.124493.5124.651.9
≥30 - ≤3925013955.611784.21510.8759939.68888.999.122
≥40 - ≤491309472.39196.833.2004937.74795.924.100
Total98574275.367290.6557.415240941.537992.7235.671.7
Education
Illiterate2431365612491.2118.110.74518.53577.892012.2
Primary51039777.835890.2266.5133.323245.521793.5104.352.2
Secondary / Higher Secondary18716688.814788.61810.810.67037.46592.945.711.4
Graduate454395.643100000062137.8621000000
Total98574275.367290.6557.415240941.537992.7235.671.7
Profession
Home Maker2451255110987.21411.221.613555.112189.6118.132.2
Agriculture Laborer49539579.836091.1276.88222946.321895.293.920.9
Casual Laborer*21519590.717790.8136.752.63516.33085.738.625.7
Shop keeper3027902696.313.7001033.3101000000
Total98574275.367290.6557.415240941.537992.7235.671.7
Economic Status
Upper Class151510015100000015100151000000
Upper Middle Class20147014100000024120241000000
Middle Class18015686.714592.9106.416.45128.34792.235.912
Lower Middle Class28320672.818991.7157.3217626.96788.2810.511.3
Lower Class48735172.130988308.5123.424349.922693124.952.1
Total98574275.367290.6557.415240941.537992.7235.671.7
Parity
P0807391.36994.522.722.72227.51777.3418.214.5
P1- P 258550185.644588.8479.491.82053518992.2125.942
> P332016852.51589463.642.418256.917395.173.821.1
Total98574275.367290.6557.415240941.537992.7235.671.7

*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace, *SC – Subcentre; PHC – Primary health care; **SDH – Sub-district hospital; DH –District hospital, P: Previous viable births.

Overall, in the present study of 2500 women interviewed, almost everyone reported change in their lives during COVID-19 pandemic, either in meals, work or health care. Of all, 40.8% of women suffered PV at home with the majority (66.7%) by their husbands and 39.4% women suffered SV with the majority (80.8%) by their husbands. A significant relation was reported between young age, lower education, labor occupation, and low economic class of women with PV and SV suffered at home during the pandemic (p Less than 0.05). Furthermore, of all the women who suffered PV, 12.1% informed the police, whereas in case of SV only 7.4% of women informed the police. The majority of the women informed their family members about the PV and SV faced at home. Furthermore, of 1019 women who suffered PV, 66.1% sought healthcare from SC/PHC/SDH/DH/private dispensaries or clinics, compared to 41.5% women who suffered SV.

Discussion

From the outbreak of COVID-19 pandemic, the emerging data from all over the world has revealed an increase in all sorts of violence against women and girls, particularly domestic violence known as “Shadow Pandemic” [12]. According to a recent survey conducted by United Nations in 13 countries, COVID has made things worse for most of the women. Women reported that the most common form of violence faced during pandemic was verbal abuse (50%), followed by sexual harassment (40%), physical abuse (36%), denial of basic needs (35%) and denial of means of communication (30%). Furthermore, seven in 10 women surveyed believed violence against women was common in their community. Of every 7 in 10 women reported increase in domestic violence during the pandemic, and 3 in 5 reported increase in sexual harassment rate in public [13].

The present community-based study was conducted to explore the hardships experienced by rural women in remote areas during the COVID-19 pandemic. Young women between 20-29 years, with less education, agricultural laborers, with many births and belonging to low economic were the ones who suffered the maximum during pandemic in terms of change in home environment, work as well as meals. They were also the ones who suffered the maximum PV and SV at the hands of their husbands and relatives. Of 2500 women interviewed, 40.8% suffered PV with the majority (66.7%) by their husbands, and 39.4% women suffered SV. The most common mode of PV suffered at home was slapping or hitting or kicking. Majority of women who suffered PV and SV informed their family members about the incident, but it was reported that only 12.1% of those who suffered PV and 7.4% who suffered SV informed the police. Furthermore, 66.1% women who suffered PV and 41.5% who suffered SV sought healthcare from SC/PHC/SDH/DH/private dispensaries or clinics.

A similar study from Ethiopia revealed that the livelihoods of 88.89% of households were severely impacted by the pandemic. The pandemic had a significant effect, compelling households to halt their livelihood activities [14]. A study revealed that during the pandemic, the indigenous population worldwide faced some of the most challenging conditions, including lack of awareness, limited availability of non-farm activities, insufficient nutritional facilities, inadequate health infrastructure, restricted access to forest areas, and a reliance on herbal medicines [15]. A recent study in the United Kingdom revealed that the pandemic disproportionately affected women. These findings underscored the gendered experiences of the COVID-19 pandemic [16]. Similar to the present study, many recent studies reported a significant rise in the intimate partner physical and sexual violence against women and children during the COVID-19 pandemic [17,18]. A similar study indicated an increase in family violence during the pandemic, driven by factors such as disaster-related instability, economic stress, reduced support options, and heightened exposure to exploitative relationships. Additionally, social isolation measures implemented globally to curb the spread of COVID-19, confined people in volatile family situations at their homes. This isolation further exacerbated their personal and collective vulnerabilities while limiting accessible and familiar support options [19]. Another recent study from the United States revealed an increase in SV and PV during the early stages of the pandemic. According to the survey, 18% of participants reported experiencing IPV. Among these, 54% said the level of victimization remained the same since the COVID-19 outbreak, 17% reported it worsened, and 30% said it improved [20]. In the present community-based study in remote villages, the numbers were much higher. Also, PV and SV as such was not uncommon and it further increased. Additionally, health care was affected a lot.

Conclusion

The present community-based study depicts the impact of COVID-19 pandemic in the rural women of India. The pandemic had significant impact on the everyday lives of women, 40.8% and 39.4% of women were found to have suffered PV and SV at home respectively during the COVID-19 pandemic, with the majority by their husbands.  They also reported increased PV and SV during pandemic compared to pre-pandemic period. Some did inform about the PV and SV at home to their family members, only 12.1% of those who suffered PV and 7.4% who suffered SV, informed the police. Demographic features like age, education, occupation, and socio-economic status did influence on the burden of PV and SV against women during the COVID-19 pandemic. It is therefore necessary to generate awareness and modes for the protection of women during pandemics.

Declarations

Funding

There was only a little honorarium for research assistant. 

Conflicts of interest/competing interests

Authors have no conflicts of interest to disclose.

References