Research Article | DOI: https://doi.org/10.31579/2690-8808/262
1Senior Consultant, Obstetrics Gynecology, TapanBhai Mukesh Bhai Patel Memorial Hospital, Medical College and Research Centre Shirpur, Dhule, Maharashtra, India.
2Additional Professor, Obstetrics Gynaecology, All India Institute of Medical Sciences, Bibinagar-508126 Hyderabad Metropolitan Region, Telangana, India.
*Corresponding Author: Shakuntala Chhabra, Senior Consultant, Obstetrics Gynecology, TapanBhai Mukesh Bhai Patel Memorial Hospital, Medical College and Research Centre Shirpur, Dhule, Maharashtra, India.
Citation: Shakuntala Chhabra and Kumar N, (2025), Sufferings of Elderly Rural women due to COVID-19 in Communities of a Remote Region: An Observational Study, J, Clinical Case Reports and Studies, 6(5); DOI:10.31579/2690-8808/262
Copyright: ©, 2025, Shakuntala Chhabra. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received: 12 June 2025 | Accepted: 19 June 2025 | Published: 30 June 2025
Keywords: Pandemic, COVID-19; elderly women; suffering; physical violence; sexual violence
Background: COVID-19 pandemic caused an unprecedented impact on society globally.
Objective: Study was conducted to know about sufferings experienced by rural elderly women in a remote hilly region.
Methodology: Community-based, cross-sectional, observational study included 4500 randomly selected tribal women of ≥50, who resided in 140 villages and consented to participate. Face-to-face interviews of participants were conducted, for 15-30 minutes, using a semi-structured questionnaire regarding sufferings of elderly women during COVID-19 pandemic.
Results: Of 4500 women interviewed, majority (47.2%) were 50-59 years old, low educated (40.4%), agriculture labourers (44.1%) and of lower economic class (53.8%). Of all participants, 73.5% reported change in everyday life, 25.9% change in meals, 30.7% in work and working environment and 39.5% in health care. Of all the women interviewed, 45.9% reported physical violence (PV), majority (74.1%) by husbands, 0.4% suffered sexual violence (SV). Modes of PV were mostly slapping, hitting, or kicking. Of all the women, who suffered PV, SV, and majority informed their family members, but only 7.0% informed police, however 98.6% who suffered sought healthcare. Socio-demographic factors like age, education, economic class, and occupation had a significant relationship with sufferings of women during pandemic.
Conclusion: Covid -19 Pandemic had significant impact on rural elderly women’s lives, 45.9% and 0.4% of women respectively reported having suffered PV and SV at home during pandemic. It is therefore necessary to generate awareness, formulate laws, policies for protection of elderly women during such pandemic.
Aging naturally brings changes to body and its functions, influencing health, wellness, and overall quality of life. The COVID-19 pandemic disrupted the lives of older adults by further restricting their movements and limiting social interactions, with particularly severe effects on rural elderly women who often live in isolation. [1]
Elderly women faced unique hardships, as the pandemic compounded everyday challenges and heightened their vulnerability. However, studies showed that providing accurate and reliable information helped reduce pandemic-related fears, especially among elderly women with chronic conditions. [2]
The COVID-19 pandemic disrupted lives across all age groups worldwide, but older adults and women have been particularly hard hit. Their heightened vulnerability stemmed from several factors. Compared to younger individuals, older adults are more likely to live with chronic health conditions, and their aging immune systems struggle to fend off illnesses, infections, and viruses effectively. When they fall ill, recovery tends to be slower and more complex, often leading to prolonged health challenges. [3] The COVID-19 pandemic disrupted access to essential healthcare and long-term care services. Beyond physical health, the pandemic exacerbated social isolation. Many older women, especially those living alone, saw their daily routines shrink, with fewer walks, limited outings, and minimal face-to-face interactions. This isolation contributed to rising feelings of loneliness and a surge in mental health challenges. Although stress related to work and finances may have been less acute for this age group compared to younger adults, the emotional strain of isolation and health-related anxieties were deeply felt. [4] The COVID-19 pandemic exposed older adults to a range of challenges, including abuse, neglect, insecurity, and health issues within their families and communities. [5] Widespread fear, anxiety, loneliness, and increased dependence have intensified these struggles, highlighting a serious societal concern. Factors such as social isolation, cognitive decline, physical frailty, and reliance on caregivers heightened the risk of elder abuse. [6, 7]
Objective
A community-based study was conducted to explore the sufferings of elderly women during the COVID-19 pandemic in a rural remote region.
Study design: Observational cross-sectional study
Study setting and duration: The study was conducted over 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 centre.
Inclusion criteria: - Randomly 30-35 women of ≥50 years of age from each village, willing for interview, were enrolled as study participants, as some villages were small and others large.
Exclusion criteria: - Women abive50 years of age, those with mental health conditions, and individuals unwilling to participate were excluded from the study.
Sample size: The calculated sample size was 4500 with 95 % confidence and 2 % absolute precision. The sample size was rounded after calculating using a free online statistical calculator (statulator) [8]
Data Collection
After the Institutional ethical committee’s approval and informed consent from the participants, socio-demographic features of all the participants including age, education, occupation, economic status, and parity were collected by a research assistant (trained nurse midwife) and were recorded on a pre-designed tool, a semi-structured questionnaire with some open and others close-ended questions. Face-to-face interviews of the study subjects were conducted regarding the sufferings faced by the elderly women during the COVID-19 pandemic. Information was collected about changes in everyday work, health care, physical violence (PV) and sexual violence (SV) against them at home, and the action taken. Each interview lasted for around 15 minutes, maintaining confidentiality and privacy in an area convenient to participants and the research assistant who recorded information on the hard tool.
Of all the women interviewed, the majority (47.2%) were of50-59 years of age, educated up to primary level (40.4%), agriculture labourer (44.1%), belonged to low economic class (53.8%) and had one or two births (52.0%). Of the 4500 women interviewed, 3306(73.5%) reported changes in their everyday lives during the COVID-19 pandemic, 856 (25.9%) reported changes in their meals due to lockdown, loss of family members employment, problems in agriculture, and poverty. Of 3306 women, 1015(30.7%) reported change in their work and working environment due to lockdown and loss of jobs and 1306(39.5%) reported change in health care due to lock down as many were not able to reach hospitals for their ailments There was lack of available health services with financial constraints also. The remaining 129(3.9%) 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 4500 women, a total of 2066 (45.9%) reported increased PV at their homes during the pandemic compared to the pre-pandemic period. Of these 2066 women, 1530 (74.1%) reported PV by their husbands, 150(7.3%) by sons, or sons-in-law, 361 (17.5%) by daughters, and daughters-in-law and in the remaining 25(1.2%) other relatives, grandsons, and grand-daughters were responsible. Table II depicts the relationship between the various socio-demographic features of women and PV at home by family members (Table II). When interviewed about the frequency and mode of PV at home, of 2066 women, 1690 (81.8%) reported once or occasional episodes of PV, 376 (18.2%) reported regular PV at home. The majority (80.2%) reported slapping, hitting by hands, or kicking as the most common modes of PV followed by hitting with bar rods or burning (18.8%) and the remaining 1.0% reported other modes like hitting with brooms, foot wares, utensils, etc. The majority of these sufferers were of 50-59 years of age, had low education, were agricultural laborers by occupation, and belonged to a low economic class. Table II depicts the relationship of socio-demographic features of women with the frequency and mode of PV suffered at home (Table II). Furthermore, of the total of 4500 women interviewed, 17(0.4%) reported SV at their homes during the pandemic, all reporting the start of SV during the pandemic, none in the pre-pandemic period. Of these 17 women, all (100%) reported SV during sleep hours and by persons other than their husbands including neighbours, distant relatives, or unknown. Table III depicts the relationship between the socio-demographic features of women and SV at home (Table III). All these women who suffered SV belonged to 50-59 years of age, the majority were illiterate (59.0%), homemakers (59.0%), belonged to a lower economic class (82.3%) and had previous one of two childbirths (88.2%).
Of all the women who suffered PV and SV, (2083) informed someone, including family members (92.1%), police (7.0%), and others like neighbours, friends, and distant relatives (0.9%) (Table IV). Of these 2083 women, 2053(98.6%) sought healthcare, 64.4% from Sub centres (SC) or Primary Health Centres (PHC), 29.5% from Sub-district hospital (SDH)/District hospital (DH), and the remaining 6.1% from private hospitals or dispensaries. The relationship between the action taken and health care sought for PV and SV suffered at home and demographic factors is shown in Table IV (Table IV).
Table I: Changes in Everyday Life of Elderly Women during the COVID-19 Pandemic
| Variables | Total | Types | |||||||||
| Age (Years) | Every Day Life | % | Meals | % | Work | % | Health Care | Others | % | ||
| ≥50-≤59 | 2123 | 1503 | 70.8 | 310 | 20.6 | 293 | 19.5 | 822 | 54.7 | 78 | 5.2 |
| ≥60-≤69 | 1565 | 1302 | 83.2 | 469 | 36.0 | 448 | 34.4 | 342 | 26.3 | 43 | 3.3 |
| ≥70 | 812 | 501 | 61.7 | 77 | 15.4 | 274 | 54.7 | 142 | 28.3 | 08 | 1.6 |
| Total | 4500 | 3306 | 73.5 | 856 | 25.9 | 1015 | 30.7 | 1306 | 39.5 | 129 | 3.9 |
| Education | |||||||||||
| Illiterate | 1495 | 1184 | 79.2 | 338 | 28.5 | 401 | 33.9 | 407 | 34.4 | 38 | 3.2 |
| Primary | 1818 | 1220 | 67.1 | 228 | 18.7 | 324 | 26.5 | 605 | 49.6 | 63 | 5.2 |
| Secondary / Higher Secondary | 997 | 809 | 81.1 | 273 | 33.7 | 257 | 31.8 | 251 | 31.0 | 28 | 3.5 |
| Graduate | 190 | 93 | 48.9 | 17 | 18.3 | 33 | 35.5 | 43 | 46.2 | 0 | 0.0 |
| Total | 4500 | 3306 | 73.5 | 856 | 25.9 | 1015 | 30.7 | 1306 | 39.5 | 129 | 3.9 |
| Profession | |||||||||||
| Home Maker | 1340 | 982 | 73.3 | 170 | 17.3 | 363 | 36.9 | 392 | 39.9 | 57 | 5.8 |
| Agriculture Laborer | 1986 | 1520 | 76.5 | 312 | 20.5 | 487 | 32.0 | 649 | 42.7 | 72 | 4.7 |
| Casual Laborer* | 1014 | 719 | 70.9 | 304 | 42.3 | 155 | 21.6 | 260 | 36.2 | 0 | 0.0 |
| Shop Keeper | 160 | 85 | 53.1 | 70 | 82.3 | 10 | 11.8 | 5 | 5.9 | 0 | 0.0 |
| Total | 4500 | 3306 | 73.5 | 856 | 25.9 | 1015 | 30.7 | 1306 | 39.5 | 129 | 3.9 |
| Economic Status | |||||||||||
| Upper Class | 92 | 68 | 73.9 | 2 | 2.9 | 12 | 17.6 | 52 | 76.5 | 2 | 2.9 |
| Upper Middle Class | 142 | 108 | 76.1 | 9 | 8.3 | 25 | 23.1 | 72 | 66.7 | 2 | 1.8 |
| Middle Class | 625 | 433 | 69.3 | 110 | 25.4 | 84 | 19.4 | 211 | 48.7 | 28 | 6.5 |
| Lower Middle Class | 1219 | 870 | 71.4 | 246 | 28.3 | 221 | 25.4 | 346 | 39.8 | 57 | 6.5 |
| Lower Class | 2422 | 1827 | 75.4 | 489 | 26.8 | 673 | 36.8 | 625 | 34.2 | 40 | 2.2 |
| Total | 4500 | 3306 | 73.5 | 856 | 25.9 | 1015 | 30.7 | 1306 | 39.5 | 129 | 3.9 |
| Parity | |||||||||||
| P 0 | 690 | 577 | 83.6 | 197 | 34.1 | 247 | 42.8 | 102 | 17.7 | 31 | 5.4 |
| P 1 - P 2 | 2341 | 1658 | 70.8 | 423 | 25.5 | 416 | 25.1 | 762 | 45.9 | 57 | 3.4 |
| >P 3 | 1469 | 1071 | 72.9 | 236 | 22.0 | 352 | 32.9 | 442 | 41.3 | 41 | 3.8 |
| Total | 4500 | 3306 | 73.5 | 856 | 25.9 | 1015 | 30.7 | 1306 | 39.5 | 129 | 3.9 |
*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace
Table II: Physical Violence against Elderly Women at Home during COVID-19
| Variables | Total | Physical Violence
| Frequency | Mode Of Violence | |||||||||||||||||
| Age (Years) | Yes | % | If Yes | Once | % | More times / Regular | % | Slap / Hitting / Kicking | % | Bar / Rod / Burns | % | Others | % | ||||||||
| Husband | % | Son / Son in law | % | Daughter / Daughter in law | % | Others | % | ||||||||||||||
| ≥50-≤59 | 2123 | 940 | 44.3 | 727 | 77.3 | 80 | 8.5 | 121 | 12.9 | 12 | 1.3 | 814 | 86.6 | 126 | 13.4 | 800 | 85.1 | 130 | 13.8 | 10 | 1.1 |
| ≥60-≤69 | 1565 | 608 | 38.8 | 404 | 66.4 | 45 | 7.4 | 150 | 24.7 | 9 | 1.5 | 453 | 74.5 | 155 | 25.5 | 441 | 72.5 | 159 | 26.2 | 8 | 1.3 |
| ≥70 | 812 | 518 | 63.8 | 399 | 77.0 | 25 | 4.8 | 90 | 17.4 | 4 | 0.8 | 423 | 81.7 | 95 | 18.3 | 415 | 80.1 | 100 | 19.3 | 3 | 0.6 |
| Total | 4500 | 2066 | 45.9 | 1530 | 74.1 | 150 | 7.3 | 361 | 17.5 | 25 | 1.2 | 1690 | 81.8 | 376 | 18.2 | 1656 | 80.2 | 389 | 18.8 | 21 | 1.0 |
| Education | |||||||||||||||||||||
| Illiterate | 1495 | 761 | 50.9 | 577 | 75.8 | 56 | 7.4 | 110 | 14.5 | 18 | 2.4 | 646 | 84.9 | 115 | 15.1 | 626 | 82.3 | 120 | 15.8 | 15 | 2.0 |
| Primary | 1818 | 1036 | 57.0 | 721 | 69.6 | 69 | 6.7 | 241 | 23.3 | 5 | 0.5 | 791 | 76.4 | 245 | 23.6 | 782 | 75.5 | 250 | 24.1 | 4 | 0.4 |
| Secondary / Higher Secondary | 997 | 259 | 26.0 | 222 | 85.7 | 25 | 9.7 | 10 | 3.9 | 2 | 0.8 | 243 | 93.8 | 16 | 6.2 | 238 | 91.9 | 19 | 7.3 | 2 | 0.8 |
| Graduate | 190 | 10 | 5.3 | 10 | 100.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 10 | 100.0 | 0 | 0.0 | 10 | 100.0 | 0 | 0.0 | 0 | 0.0 |
| Total | 4500 | 2066 | 45.9 | 1530 | 74.1 | 150 | 7.3 | 361 | 17.5 | 25 | 1.2 | 1690 | 81.8 | 376 | 18.2 | 1656 | 80.2 | 389 | 18.8 | 21 | 1.0 |
| Profession | |||||||||||||||||||||
| Home Maker | 1340 | 955 | 71.3 | 655 | 68.6 | 60 | 6.3 | 221 | 23.1 | 19 | 2.0 | 731 | 76.5 | 224 | 23.5 | 709 | 74.2 | 229 | 24.0 | 17 | 1.8 |
| Agriculture Labourer | 1986 | 761 | 38.3 | 577 | 75.8 | 55 | 7.2 | 123 | 16.2 | 6 | 0.8 | 634 | 83.3 | 127 | 16.7 | 628 | 82.5 | 129 | 17.0 | 4 | 0.5 |
| Casual Labourer* | 1014 | 315 | 31.1 | 263 | 83.5 | 35 | 11.1 | 17 | 5.4 | 0 | 0.0 | 290 | 92.1 | 25 | 7.9 | 285 | 90.5 | 30 | 9.5 | 0 | 0.0 |
| Shop Keeper | 160 | 35 | 21.9 | 35 | 100.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 35 | 100.0 | 0 | 0.0 | 34 | 97.1 | 1 | 2.9 | 0 | 0.0 |
| Total | 4500 | 2066 | 45.9 | 1530 | 74.1 | 150 | 7.3 | 361 | 17.5 | 25 | 1.2 | 1690 | 81.8 | 376 | 18.2 | 1656 | 80.2 | 389 | 18.8 | 21 | 1.0 |
| Economic Status | |||||||||||||||||||||
| Upper Class | 92 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 |
| Upper Middle Class | 142 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 |
| Middle Class | 625 | 320 | 51.2 | 300 | 93.8 | 15 | 4.7 | 4 | 1.3 | 1 | 0.3 | 314 | 98.1 | 6 | 1.9 | 309 | 96.6 | 10 | 3.1 | 1 | 0.3 |
| Lower Middle Class | 1219 | 1415 | 116.1 | 990 | 70.0 | 110 | 7.8 | 301 | 21.3 | 14 | 1.0 | 1106 | 78.2 | 309 | 21.8 | 1088 | 76.9 | 315 | 22.3 | 12 | 0.8 |
| Lower Class | 2422 | 331 | 13.7 | 240 | 72.5 | 25 | 7.6 | 56 | 16.9 | 10 | 3.0 | 270 | 81.6 | 61 | 18.4 | 259 | 78.2 | 64 | 19.3 | 8 | 2.4 |
| Total | 4500 | 2066 | 45.9 | 1530 | 74.1 | 150 | 7.3 | 361 | 17.5 | 25 | 1.2 | 1690 | 81.8 | 376 | 18.2 | 1656 | 80.2 | 389 | 18.8 | 21 | 1.0 |
| Parity | |||||||||||||||||||||
| P 0 | 690 | 218 | 31.6 | 134 | 61.5 | 35 | 16.1 | 47 | 21.6 | 2 | 0.9 | 168 | 77.1 | 50 | 22.9 | 162 | 74.3 | 54 | 24.8 | 2 | 0.9 |
| P 1- P2 | 2341 | 1126 | 48.1 | 844 | 75.0 | 75 | 6.7 | 189 | 16.8 | 18 | 1.6 | 930 | 82.6 | 196 | 17.4 | 910 | 80.8 | 201 | 17.9 | 15 | 1.3 |
| >P3 | 1469 | 722 | 49.1 | 552 | 76.5 | 40 | 5.5 | 125 | 17.3 | 5 | 0.7 | 592 | 82.0 | 130 | 18.0 | 584 | 80.9 | 134 | 18.6 | 4 | 0.6 |
| Total | 4500 | 2066 | 45.9 | 1530 | 74.1 | 150 | 7.3 | 361 | 17.5 | 25 | 1.2 | 1690 | 81.8 | 376 | 18.2 | 1656 | 80.2 | 389 | 18.8 | 21 | 1.0 |
*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace
Table III: Sexual Violence against Elderly Women at Home during COVID-19 Pandemic
| Variables | TTotal | Sexual Violence | Marital sexual violence** | Person *** | ||||
| Age (Years) | Yes | % | Timing | If, Yes *** | ||||
| Sleeping only time | % | Others | % | |||||
| ≥50-≤59 | 2123 | 17 | 0.8 | 17 | 100.0 | 17 | 100.0 | |
| ≥60-≤69 | 1565 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
| ≥70 | 812 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
| Total | 4500 | 17 | 0.4 | 17 | 100.0 | 17 | 100.0 | |
| Education | ||||||||
| Illiterate | 1495 | 10 | 0.7 | 10 | 100.0 | 10 | 100.0 | |
| Primary | 1818 | 7 | 0.4 | 7 | 100.0 | 7 | 100.0 | |
| Secondary/Higher Secondary | 997 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
| Graduate | 190 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
| Total | 4500 | 17 | 0.4 | 17 | 100.0 | 17 | 100.0 | |
| Profession | ||||||||
| Home Maker | 1340 | 10 | 0.7 | 10 | 100.0 | 10 | 100.0 | |
| Agriculture Laborer | 1986 | 5 | 0.3 | 5 | 100.0 | 5 | 100.0 | |
| Casual Laborer* | 1014 | 2 | 0.2 | 2 | 100.0 | 2 | 100.0 | |
| Shop Keeper | 160 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
| Total | 4500 | 17 | 0.4 | 17 | 100.0 | 17 | 100.0 | |
| Economic Status | ||||||||
| Upper Class | 92 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
| Upper Middle Class | 142 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
| Middle Class | 625 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
| Lower Middle Class | 1219 | 3 | 0.2 | 3 | 100.0 | 3 | 100.0 | |
| Lower Class | 2422 | 14 | 0.6 | 14 | 100.0 | 14 | 100.0 | |
| Total | 4500 | 17 | 0.4 | 17 | 100.0 | 17 | 100.0 | |
| Parity | ||||||||
| P 0 | 690 | 2 | 0.3 | 2 | 100.0 | 2 | 100.0 | |
| P 1- P 2 | 2341 | 15 | 0.6 | 15 | 100.0 | 15 | 100.0 | |
| >P3 | 1469 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
| Total | 4500 | 17 | 0.4 | 17 | 100.0 | 17 | 100.0 | |
*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace
** Only sleeping time
*** No relative was responsible
Table IV: Action taken by Elderly Women against Physical and Sexual Violence
| Variables | Total | Informed Someone | Health Care Sought | ||||||||||||||
| Age (Years) | Yes | % | Family Member | % | Police | % | Other | % | Yes | % | *SC /**PHC | % | ***SDH / ****DH | % | Others | % | |
| ≥50-≤59 | 2123 | 957 | 45.1 | 868 | 90.7 | 79 | 8.3 | 10 | 1.0 | 947 | 99.0 | 610 | 64.4 | 260 | 27.5 | 77 | 8.1 |
| ≥60-≤69 | 1565 | 608 | 38.8 | 556 | 91.4 | 45 | 7.4 | 7 | 1.2 | 598 | 98.4 | 458 | 76.6 | 98 | 16.4 | 42 | 7.0 |
| ≥70 | 812 | 518 | 63.8 | 495 | 95.6 | 21 | 4.1 | 2 | 0.4 | 508 | 98.1 | 254 | 50.0 | 248 | 48.8 | 6 | 1.2 |
| Total | 4500 | 2083 | 46.3 | 1919 | 92.1 | 145 | 7.0 | 19 | 0.9 | 2053 | 98.6 | 1322 | 64.4 | 606 | 29.5 | 125 | 6.1 |
| Education | |||||||||||||||||
| Illiterate | 1495 | 771 | 51.6 | 702 | 91.1 | 54 | 7.0 | 15 | 1.9 | 761 | 98.7 | 576 | 75.7 | 150 | 19.7 | 35 | 4.6 |
| Primary | 1818 | 1043 | 57.4 | 970 | 93.0 | 70 | 6.7 | 3 | 0.3 | 1033 | 99.0 | 625 | 60.5 | 346 | 33.5 | 62 | 6.0 |
| Secondary / Higher Secondary | 997 | 259 | 26.0 | 237 | 91.5 | 21 | 8.1 | 1 | 0.4 | 249 | 96.1 | 116 | 46.6 | 105 | 42.2 | 28 | 11.2 |
| Graduate | 190 | 10 | 5.3 | 10 | 100.0 | 0 | 0.0 | 0 | 0.0 | 10 | 100.0 | 5 | 50.0 | 5 | 50.0 | 0 | 0.0 |
| Total | 4500 | 2083 | 46.3 | 1919 | 92.1 | 145 | 7.0 | 19 | 0.9 | 2053 | 98.6 | 1322 | 64.4 | 606 | 29.5 | 125 | 6.1 |
| Profession | |||||||||||||||||
| Home Maker | 1340 | 965 | 72.0 | 892 | 92.4 | 58 | 6.0 | 15 | 1.6 | 955 | 99.0 | 652 | 68.3 | 248 | 26.0 | 55 | 5.8 |
| Agriculture Laborer | 1986 | 766 | 38.6 | 708 | 92.4 | 54 | 7.0 | 4 | 0.5 | 756 | 98.7 | 391 | 51.7 | 295 | 39.0 | 70 | 9.3 |
| Casual Laborer* | 1014 | 317 | 31.3 | 284 | 89.6 | 33 | 10.4 | 0 | 0.0 | 312 | 98.4 | 254 | 81.4 | 58 | 18.6 | 0 | 0.0 |
| Shop Keeper | 160 | 35 | 21.9 | 35 | 100.0 | 0 | 0.0 | 0 | 0.0 | 30 | 85.7 | 25 | 83.3 | 5 | 16.7 | 0 | 0.0 |
| Total | 4500 | 2083 | 46.3 | 1919 | 92.1 | 145 | 7.0 | 19 | 0.9 | 2053 | 98.6 | 1322 | 64.4 | 606 | 29.5 | 125 | 6.1 |
| Economic Status | |||||||||||||||||
| Upper Class | 92 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 |
| Upper Middle Class | 142 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 |
| Middle Class | 625 | 320 | 51.2 | 306 | 95.6 | 14 | 4.4 | 0 | 0.0 | 310 | 96.9 | 226 | 72.9 | 56 | 18.1 | 28 | 9.0 |
| Lower Middle Class | 1219 | 1418 | 116.3 | 1296 | 91.4 | 108 | 7.6 | 14 | 1.0 | 1408 | 99.3 | 1199 | 85.2 | 152 | 10.8 | 57 | 4.0 |
| Lower Class | 2422 | 345 | 14.2 | 317 | 91.9 | 23 | 6.7 | 5 | 1.4 | 335 | 97.1 | -103 | -30.7 | 398 | 118.8 | 40 | 11.9 |
| Total | 4500 | 2083 | 46.3 | 1919 | 92.1 | 145 | 7.0 | 19 | 0.9 | 2053 | 98.6 | 1322 | 64.4 | 606 | 29.5 | 125 | 6.1 |
| Parity | |||||||||||||||||
| P 0 | 690 | 220 | 31.9 | 188 | 85.5 | 31 | 14.1 | 1 | 0.5 | 210 | 95.5 | 135 | 64.3 | 45 | 21.4 | 30 | 14.3 |
| P 1- P 2 | 2341 | 1141 | 48.7 | 1053 | 92.3 | 74 | 6.5 | 14 | 1.2 | 1131 | 99.1 | 775 | 68.5 | 300 | 26.5 | 56 | 5.0 |
| >P3 | 1469 | 722 | 49.1 | 678 | 93.9 | 40 | 5.5 | 4 | 0.6 | 712 | 98.6 | 450 | 63.2 | 223 | 31.3 | 39 | 5.5 |
| Total | 4500 | 2083 | 46.3 | 1919 | 92.1 | 145 | 7.0 | 19 | 0.9 | 2053 | 98.6 | 1360 | 66.2 | 568 | 27.7 | 125 | 6.1 |
*Small Scale, (Food, Shoes making, Bamboo items) Industry, Welding Workshop, Brick furnace
*SC – Subcentre **PHC – Primary Health Care
****DH – District Hospital ***SDH – Sub District Hospital
Overall, in the present study of 4500 women interviewed, almost everyone reported change in their lives during the COVID-19 pandemic, either in meals, work, or health care. Of all, 45.9% of women suffered PV at home with the majority (74.1%) by their husbands and 0.4% of women suffered SV all by persons other than their husbands. A significant relation was reported with age, low education, occupation, and low economic class of women who suffered PV and SV at home during the pandemic (p < 0.05). Furthermore, of all the women who suffered PV and /or SV, only 7.0% informed the police. The majority of the women informed their family members about the PV and SV faced at home (92.1%). Furthermore, of all the women who suffered PV and or SC, 98.6% sought healthcare from SC/PHC/SDH/DH/private dispensaries or clinics.
Elder abuse is a critical public health issue with far-reaching social, economic, and health consequences. Before the COVID-19 pandemic, one in ten older Americans experienced elder abuse annually. According to the World Health Organization, elder abuse involves a single or repeated act or a failure to act within a trusted relationship that results in harm or distress to an older adult. [9, 10] The pandemic exacerbated these challenges, with studies highlighting significant declines in both physical and mental health among older women. A survey of 40,821 elderly women in England, with an average age of 76, found that 28 % reported a decline in physical health, while 26 % experienced worsening mental health during the pandemic. [11] Another longitudinal study involving 5,146 women in England revealed a sharp increase in mental health issues, with clinically significant depressive symptoms rising from 12.5 % before the pandemic to 28.5 % during it. This surge was accompanied by increased loneliness, diminished quality of life, and higher anxiety levels, with prevalence growing from 9.4 % to 10.9 % . Widows were particularly vulnerable to negative mental health impacts. [12]
The present community-based study explored the hardships faced by rural elderly women in a remote region during the COVID-19 pandemic. Elderly women aged 50-59, with low education levels, employed as agricultural laborers, having one or two children, and belonging to low socioeconomic backgrounds, were most affected by changes in home environments, work, and meals. These women also reported high rates of PV from husbands and relatives. Among 4500 women interviewed, 45.9 % experienced primarily through slapping, hitting, or kicking with 74.1 % of incidents involving their husbands. Additionally, 0.4 % suffered SV. Many informed family members about these incidents, but only 7.0 % of the victims who suffered PV/SV reported the abuse to the police. However, 98.6 % of PV and SV affected women sought healthcare from primary and secondary healthcare facilities or private clinics.
A study from India echoed these findings, highlighting how older adults, particularly women, faced abuse during the pandemic due to fears of infection, financial strain, and caregiver neglect. Tragically, much of this abuse came from family members, neighbors, and caregivers [1,3]. Similarly, research in Northern Thailand’s hilly tribal communities revealed that elderly women, especially those with limited education and poor economic backgrounds, struggled significantly during the pandemic.[14]
In Malaysia, beyond the direct morbidity and mortality from COVID-19, older adults suffered due to lockdowns, movement restrictions, economic shutdowns, and disruptions to non-essential services. Elderly women were particularly vulnerable to social isolation, compounded by chronic diseases, physical limitations, caregiver dependency, and institutionalization.[15]
A cross-sectional survey in Sweden during the pandemic’s early phase showed that elderly women were at higher risk of mental health issues. Half of the participants reported staying home constantly, and many felt depressed, struggled with sleep, and suffered from isolation. While elderly individuals generally adhered to social distancing recommendations, this compliance risked deteriorating mental health and potential long-term effects. [16]
Another study which focused on immigrants of aged 60 and older from Cuba, the Dominican Republic, El Salvador, Mexico, Puerto Rico, and Venezuela revealed that respondents endured unemployment, hunger, and income loss. [17] The present study in remote villages reflected even higher rates of hardship, with PV and SV being alarmingly common and healthcare access significantly disrupted.
The findings underscore the need for targeted interventions to support older adults, particularly rural and marginalized women, by enhancing healthcare access, promoting safety, and addressing mental health needs during and beyond public health crises.
This community-based study highlights the profound impact of the COVID-19 pandemic on rural elderly women in India. The pandemic disrupted everyday life, with 45.9% of elderly women experiencing increased primarily at the hands of their husbands and 0.4% SV. While the majority of the victims confided in family members, only a small fraction (7.0%) reported incidents to the police.
Key demographic factors such as age, education, occupation, and socioeconomic status significantly influenced the prevalence of abuse. These findings emphasize the need for increased awareness and the development of robust support systems and protective measures for elderly women during public health crises. Establishing clear reporting channels, promoting community-based support, and enforcing legal protections are critical to safeguarding vulnerable populations in future emergencies.
There was only a little honorarium for research assistant.
Authors have no conflicts of interest to disclose.
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