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Policy: Original article
158 (
3
); 217-227
doi:
10.4103/ijmr.ijmr_3299_21

Verbal autopsy to assess causes of mortality among the economically productive age group in the tribal region of Melghat, central India

Department of Medicine, Mahatma Gandhi Tribal Hospital, Amravati, Maharashtra, India
Department of Community Health, Mahatma Gandhi Tribal Hospital, Amravati, Maharashtra, India
Department of Ophthalmology, Mahatma Gandhi Tribal Hospital, Amravati, Maharashtra, India
Department of Research, MAHAN Trust, Amravati, Maharashtra, India
Department of Paediatric Infectious Diseases, University of Colorado School of Medicine and Children’s Hospital Colorado, Aurora, Colorado, USA
Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado, USA

For correspondence: Dr Ashish Rambhau Satav, Mahatma Gandhi Tribal Hospital, Karmgram, Utavali, Dharni, Amaravati 444 702, Maharashtra, India e-mail: drashish@mahantrust.org

Licence
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Disclaimer:
This article was originally published by Wolters Kluwer - Medknow and was migrated to Scientific Scholar after the change of Publisher.

Abstract

Background & Objectives:

Verbal autopsy (VA) is the systematic and retrospective inquiry (from relatives) about the symptoms of an illness prior to death. In tribal India, 67-75 per cent of deaths occur at home with an unknown cause of death (CoD). Hence, the aim of this study was to determine the CoD in the 16-60 yr age group utilizing VA.

Methods:

A prospective, community based longitudinal study was conducted in 32 tribal villages in the Melghat region of Maharashtra, between 2004 and 2020. Number of deaths and VAs in 16-60 yr age group were collected by village health workers (VHWs) and supervisors, verified by five different persons (internal-external) and cross-checked by three VA interpretation trained physicians. A modified version of WHO VA was used. Cause-specific mortality fractions were calculated.

Results:

Of the 1011 deaths recorded, mortality in males was significantly higher than females (P<0.001). A total of 763 VAs were conducted which revealed that tuberculosis was the leading CoD, followed by jaundice, heart diseases, diarrhoea, central nervous system infections and suicide. Suicides were significantly more common among males than in females (P=0.046). Significantly, more deaths occurred during the monsoon (P=0.002), especially diarrhoeal deaths (P=0.024).

Interpretation & conclusions:

The findings of this study suggest that, in Indian tribal areas, infectious diseases are the leading causes of morbidity and one of the major causes of deaths in economically productive age group. Intensified VHW-mediated interventions are required to reduce the premature deaths.

Keywords

Economically productive age group
Melghat
tribal
verbal autopsy

Understanding the cause of death (CoD) is crucial for policy framing and planning programmes to improve health indicators. A reliable assessment of disease-specific mortality rates is nearly impossible in developing countries because the underlying cause (UC) is unknown or relevant information is not recorded due to poor reach and coverage of the death registration system1. Verbal autopsy (VA) is a retrospective inquiry systematically conducted involving the family members of the deceased to collect information pertaining to the symptoms before death through predetermined questions to describe the CoD for home deaths2,3. VA will enable evidence-based decision-making and can guide public health priorities in communities without physician certified deaths4,5.

In most resource constrained, hilly, forest, rural-tribal areas of world with high mortality, documentation of death information and medical certification of CoD is nearly impossible because of linited healthcare access, low health literacy in tribal populations and a high proportion (67 to 75%) of deaths which occur outside of the healthcare setting6,7. The physician-certified verbal autopsy (PCVA) approach is reportedly more effective in determining CoD in community deaths8.

MAHAN trust, a non-governmental organization (NGO) is continually providing holistic medical services to poor tribals of Melghat for the last 25 years, conducted a 17 yr study which revealed that the age-specific mortality rate (ASMR) in Melghat was >400/100000 population2, which is 2.25 times greater than the rest of India (178 in 2016). Deaths in the economically productive age group can have detrimental effects on the community, nation and family members, particularly children as it also reportedly increases malnutrition9 and deaths10.

This study was conducted to ascertain the CoD in the 16-60 yr age group in Melghat, which has previously been reported to have a disproportionately high age-specific mortality rate as compared to the Indian average. In order for intervention to prevent these premature deaths through the village based healthcare for the economically productive age group people (EPAGP), as a first step, VA in EPAGP was needed to know the CoDs to plan the programmes to reduce mortality. The objective of this study was to determine the underlying cause (UC) for cause-specific mortality and to determine contributory causes (CC) for all causes of mortality by VA in EPAGP in Melghat.

Material & Methods

A community based longitudinal prospective study was conducted from January 2004 to December 2020 in EPAGP in 34 villages of Melghat. The study was ethically approved by the Institutional Review Board of MAHAN trust. A written informed consent was obtained from all participants and the Gram Sabha of the villages.

Source population: Melghat is a hilly, forest, difficult to access, highly impoverished tribal area in Amravati district of Maharashtra. It is spread over 4000 km2, across 320 villages. The population is 300,000 with 84 per cent poor tribal, 50 per cent semiliterate/illiterate, mostly small farmers/labourers. Melghat has poor transportation, grossly inadequate health services and low health seeking behaviour, leading to high mortality11.

Sample size: In all 34 villages (10% of total 320 villages) from two blocks of Melghat were considered for this study (Fig. 1). A minimum of 50 per cent of total mortality was decided as the criteria for VA, considering the feasibility of such exercise in the tribal population. The World Health Organization (WHO) has recommended cluster sampling and minimum population size of 2000-20000. A two stage cluster sampling technique was employed. The first stage is a block and the second is the villages within each block. Eight clusters/villages from five zones were randomly picked up by the lottery method. Finally, 34 clusters were selected based on the willingness of the villagers and village health workers (VHWs) to participate and were block stratified. In the year 2016, two villages were dropped from the study due to administrative reasons and hence data was analysed from 32 villages. The sample unit comprised all deaths in the EPAGP in the selected villages. The total number of deaths during the period was 1011. Verbal autopsies were conducted in 763 (75.46%) deaths.

Selection of study participants.
Fig. 1
Selection of study participants.

Inclusion and exclusion criteria: De-facto method (home and hospital deaths in the study area) was used12. Only close relatives of all deceased individuals who gave consent were included in this study. Those who migrated (≥6 months ago) were excluded from the study.

Study tool and technique:

Vital event capture methodology: The VHWs, who were residents of the same villages, conducted a census (including population in EPAGP), that included a baseline door-to-door survey regarding deaths (16-60 yr) and demographic information in January 2004. They were supervised by data collection supervisors and project managers. It was reviewed by the principal investigator. Multiple methods were used for death data collection in the community to improve the accuracy of death statistics11.

Standardized VA tool developed by MAHAN was used. It was the modified version of the WHO VA tool13 adapted to the local context. The MAHAN VA tool consisted of a standardized questionnaire (open and close ended) that gathered information on symptoms, medical history and circumstances preceding the death. The tool included a set of standard algorithms for determining major CoD among EPAGP. The CoD, or the sequence of causes that led to a death, was assigned based on the data. The tool was piloted for validation by a senior physician, among 20 deaths at a medical college in Sewagram (data not shown). The CoD by VA was compared with the hospital CoD and there was >75 per cent agreement between the two. The validity of this tool was confirmed with three different physicians/co-investigators and two field staff. From 2004 to 2010, the same VA data collection tool was used. Modifications were subsequently made based on our field experience and the WHO4 and IHME methods14.

The well trained team speaking local dialect included a local tribal semiliterate VHW from each village and data collection supervisor. Grief counselling was done within 48 h of death and before conducting VA by the team, who conducted VA within seven to 15 days of the death of the person, after obtaining informed consent from the relatives. The process consisted of: (i) asking the family members open and close ended questionnaires; and (ii) its analysis15.

A trained medical supervisor cross checked the VA forms. VA with its algorithms was checked by two other VA interpretation-trained doctors who independently assessed it for CoD. If the CoD determined by two doctors concurred, then that defined the CoD. The agreement level between two coders was 89.39 per cent. In 11 per cent of VA, there was discrepancy in CoDs by two doctors. Following underlying CoDs were different in the two coders: Tetanus, central nervous system (CNS) infection vs. intracranial space occupying lesions, intestinal obstruction vs. perforation peritonitis, diabetes mellitus, tuberculosis (TB) and acquired immunodeficiency syndrome. The authors sent discrepant VAs to a third coder, an experienced physician who acted as an arbitrator. The arbitrator personally checked the VA, verified the discrepancy and finalized the CoD. There were 15 garbage codes in all deaths. However, only two of these were included in the final list and the rest were the part of a miscellaneous CoD.

As the CoD was determined by VA, it was not possible to conduct bacteriological confirmation for TB. TB was differentiated from chronic obstructive pulmonary disease (COPD) by the following history: presence of haemoptysis, significant weight loss, extreme fatigability and anorexia during the last one month, family/past history of TB, no BCG vaccination, any lump in cervicaland/axillary area, presence of any associated symptoms such as neck pain, headache, vomiting, change in voice, difficulty in deglutition, fever suggested that TB (pulmonary or extrapulmonary) was the CoD. The following history favoured COPD: excessive breathlessness leading to difficulty in day-to-day routine activities and patient had to sit for long time/days without sleeping in supine position, patient had cough with white mucoid expectoration for a minimum for two months every year which increased during winter for three consecutive years, cyanosis, recurrent breathlessness, history of smoking, etc. The table showing algorithms for TB and COPD and VA form is attached as Annexures 1 and 2.

Statistical analysis: Data entry was done using Microsoft Excel 2007. Cause-specific mortality fractions (CSMF) were calculated as the number of deaths from specific cause, divided by the total deaths, during a given time interval16. The homogeneity of event occurrence between gender types and seasons was tested using the Pearson’s Chi-square test of homogeneity. The analysis was done independently for each study period. The computations were performed using the SPSS version 26.0 (IBM Corp., Armonk, NY, USA) software and the significance was evaluated at five per cent level.

Results

The completeness of death reporting was ~95 per cent. The population of the 32 villages was 29,356, with 15,002 (51.1%) males and 14,354 (48.9%) females. The minimum sample size needed was 500 VA. Seven hundred and sixty three VA were randomly undertaken to improve the confidence interval and accuracy. There were no significant differentials in the response rates over time or by age/sex of the deceased. Only response rates varied across surveyors.

Table I shows age sex distribution of the study population and occurrence of deaths during three study periods. In the 21-30 yr category, during 2010-2015 and 2016-2020, the proportion of male deaths was significantly higher than that of females (P<0.001 and P=0.032, respectively). In the 41-50 yr category, the proportion of male deaths was significantly higher than females (P=0.034) for the period 2010-2015. In the 51-60 yr category, for the period 2016-2020, the male deaths were significantly higher than that of females (P=0.003). Overall, for the last two study periods, the male deaths were significantly higher than females. The male deaths (all age groups (16-60 yr), 21-30 and 51-60 yr groups) were significantly higher than that of females for total 17 yr (P<0.001, P<0.001 and P<0.001, respectively). There was a significant increase in deaths per 10,0000 population per year in the age group of 41-50 yr and 51-60 yr as compared to previous age groups. Table II shows the age wise distribution of cause-specific mortality during three study periods.

Table I Age-sex distribution of study population and occurrence of deaths during the three study periods
Age (yr) Gender Total population#, n (%) 2004-2009
Deaths
2010-2015
Deaths
2016-2020
Deaths
2004-2020
Deaths/100,000 population per yr Total deaths % (95% CI)
16-20 Male 1826 (21.3) 22 (10.2)** 25 (10.9) 8 (5.7) 177.18 55 3.01 (2.28-3.9)
Female 1882 (23.2) 32 (16.8) 21 (15.4) 9 (8.9) 193.79 62 3.29 (2.53-4.2)
21-30 Male 2945 (34.3) 51 (23.7) 51 (22.4)*** 31 (21.9)* 265.65 133 4.52 (3.79-5.33)***
Female 2893 (35.6) 46 (24.2) 21 (15.4) 16 (15.9) 168.76 83 2.87 (2.29-3.54)
31-40 Male 1999 (23.3) 53 (34.7) 36 (15.8) 15 (10.6) 306.04 104 5.2 (4.27-6.27)
Female 1778 (21.9) 40 (21) 23 (16.9) 20 (19.8) 274.6 83 4.67 (3.74-5.75)
41-50 Male 1234 (14.4) 57 (26.5) 55 (24.2)* 32 (22.7) 686.43 144 11.67 (9.92-13.59)
Female 1014 (12.5) 51 (26.8) 28 (20.6) 29 (28.7) 626.52 108 10.65 (8.82-12.71)
51-60 Male 575 (6.7) 32 (14.9) 61 (26.8) 55 (39) 1514.07 148 25.74 (22.21-29.52)***
Female 550 (6.8) 21 (11) 43 (31.6) 27 (26.7) 973.26 91 16.55 (13.54-19.92)
Total (16-60) Male 8579 (100) 215 (53.1) 228 (62.6) 141 (58.5) 400.43 584 6.81 (6.28-7.36)***
Female 8117 (100) 190 (46.9) 136 (37.4) 101 (41.7) 309.44 427 5.26 (4.79-5.77)

#As per census 2009; P *<0.05, **<0.01, ***<0.001. CI, confidence interval

Table II Age-wise distribution of cause-specific mortality during three study periods
Age groups (yr) Major causes of deaths 2004-2009 2010-2015 2016-2020 2004-2020 17 (yr) Deaths/100,000 population per yr UC + CC, % (95% CI)
UC CC UC CC UC CC UC CC UC CC
16-20 TB 10 5 12 10 0 1 22 16 34.9 25.38 1.02 (0.7-1.4)
Diarrhoeal disease 6 6 11 6 2 1 19 13 30.14 20.62 0.8 (0.59-1.22)
Suicide 4 4 3 3 0 0 7 7 11.1 11.1 0.38 (0.21-0.63)
Jaundice 4 2 1 2 1 1 6 5 9.52 7.93 0.30 (0.15-0.53)
21-30 TB 17 9 21 19 2 3 40 31 40.3 31.24 1.22 (0.95-1.53)
Suicide 7 7 8 8 1 1 16 16 16.12 16.12 0.55 (0.37-0.77)
Jaundice 7 5 8 4 2 4 17 13 17.13 13.1 0.51 (0.35-0.73)
Diarrhoeal disease 2 4 4 5 1 2 7 11 7.05 11.08 0.31 (0.18-0.49)
31-40 TB 10 7 12 13 4 2 26 22 40.49 34.26 1.01 (0.71-1.38)
Diarrhoeal disease 5 4 6 6 1 1 12 11 18.69 17.13 0.61 (0.39-0.91)
Jaundice 4 4 7 5 0 0 11 9 17.13 14.02 0.53 (0.32-0.82)
Suicide 4 4 2 2 1 1 7 7 10.9 10.9 0.37 (0.2-0.62)
41-50 TB 16 6 20 19 4 7 40 32 104.67 83.73 3.2 (2.51-4.02)
Heart diseases 13 11 10 9 4 6 27 26 70.65 68.03 2.36 (1.77-3.07)
Diarrhoeal diseases 5 9 4 4 1 3 10 16 26.17 41.87 1.16 (0.76-1.69)
Jaundice 2 2 10 6 1 1 13 9 34.02 23.55 0.98 (0.61-1.48)
CNS infection 4 4 4 4 10.47 10.47 0.36 (0.15-0.7)
51-60 TB 0 0 20 18 8 8 28 26 146.41 135.95 4.8 (3.63-6.22)
Heart diseases 8 15 20 13 4 4 32 32 167.32 167.32 5.69 (4.41-7.21)
Diarrhoeal diseases 8 7 4 6 1 1 13 14 67.97 73.2 2.4 (1.59-3.47)
CNS infection 3 6 4 3 3 4 10 13 52.29 67.97 2.04 (1.3-3.05)
Jaundice 3 2 7 3 1 1 11 6 57.52 31.37 1.51 (0.88-2.41)

UC, underlying cause; CC, contributory cause; TB, tuberculosis; CNS, central nervous system

CNS infections were more common among the older age groups as compared to the younger one. TB was the most common CoDs in all age groups except in the 51-60 yr age group.

Table III provides the gender-wise distribution of CoDs and CSMF during the three study periods. The subjects comprised of 41.68 per cent females and 58.32 per cent males.

Table III Gender-wise distribution of causes of deaths and cause-specific mortality fractions (CMSF) during the three study periods
Cause of death 2004-2010 2011-2015 2016-2020
UC (n) CC (n) CSMF (%) UC (n) CC (n) CSMF (%) UC (n) CC (n) CSMF (%)
Male Female Male Female Male Female Male Female Male Female Male Female
TB 20 33 11 15 13.5 50 35 48 31 22.53 11 8 8 8 16.5
Jaundice 10 10 6 9 6 27 16 13 11 9.2 4 0 2 1 3.3
IHD 15 7 10 7 6.7 17 8 14 9 6.6 3 3 6 7 9
Diarrhoeal diseases 12 14 16 14 9.6 10 5 12 5 4.4 5 2 3 5 7.1
CNS infection 11 8 16 16 8.7 9 5 13 9 4.9 1 1 4 1 3.3
Suicide 13 4 13 4 5.8 17 6 17 6 6.3 1 1 1 1 1.9
Pneumonia 4 6 16 15 7 3 0 8 4 2.1 3 5 10 6 11.3
Cancer 5 7 4 4 3.4 13 11 10 10 6 4 3 2 2 5.2
CVE 5 5 5 7 3.8 3 8 4 8 3.2 3 1 1 0 2.4
COAD 7 4 7 6 4.1 3 3 5 3 1.9 4 3 1 2 4.7
RTA 1 0 1 0 0.3 8 0 8 0 2.2 2 0 4 0 2.8
Alcohol toxication 5 0 5 0 1.7 3 1 3 1 1.1 3 1 0 1 2.4
AIDS 4 2 1 1 1.4 3 2 3 1 1.2 1 2 0 2 2.4
Tetanus 3 1 3 1 1.4 5 0 5 0 1.4 2 0 2 0 1.9
RF 1 0 2 0 0.5 5 5 5 3 2.3 0 0 0 0 0
Homicide 5 2 5 2 2.4 2 1 2 1 0.8 0 0 0 0 0
Snake bite 2 0 2 0 0.7 5 1 5 1 1.7 0 0 0 0 0
Drowning 2 1 2 1 1 3 0 3 0 0.8 0 0 0 0 0
ALD 0 0 0 0 0 5 0 5 0 1.4 1 0 0 0 0.5
Miscellaneous 35 29 35 31 22.2 37 29 45 33 19.8 9 19 13 13 25.5
Total 160 133 160 133 100 228 136 228 136 100 57 49 57 49 100
Cause of death 2004-2020
UC (n) CC (n) Total (UC + CC)
Male + female
CSMF, % (95% CI) Deaths /100,000 population per yr
Male Female Male Female
TB 81 76 67 54 278 18.22 (16.31-20.25) 97.95
Jaundice 41 26 21 21 109 7.14 (5.9-8.55) 38.4
IHD 35 18 30 23 106 6.95 (5.72-8.34) 37.35
Diarrhoeal diseases 27 21 31 24 103 6.75 (5.54-8.13) 36.29
CNS infection 21 14 33 26 94 6.16 (5.01-7.49) 33.12
Suicide 31 11 31 11 84 5.5 (4.41-6.77) 29.59
Pneumonia 10 11 34 25 80 5.24 (4.18-6.48) 28.19
Cancer 22 21 16 16 75 4.91 (3.88-6.12) 26.42
CVE 11 14 10 15 50 3.28 (2.44-4.3) 17.62
COAD 14 10 13 11 48 3.15 (2.33-4.15) 16.91
RTA 11 0 13 0 24 1.57 (1.01-2.33) 8.46
Alcohol toxication 11 2 8 2 23 1.51 (0.96-2.25) 8.1
AIDS 8 6 4 4 22 1.44 (0.91-2.17) 7.75
Tetanus 10 1 10 1 22 1.44 (0.91-2.17) 7.75
RF 6 5 7 3 21 1.38 (0.85-2.1) 7.4
Homicide 7 3 7 3 20 1.31 (0.8-2.02) 7.05
Snake bite 7 1 7 1 16 1.05 (0.60-1.7) 5.64
Drowning 5 1 5 1 12 0.79 (0.4-1.37) 4.23
ALD 6 0 5 0 11 0.72 (0.36-1.29) 3.88
Miscellaneous 81 77 93 77 328 21.49 (19.46-23.64) 115.56
Total 445 318 445 318 100

RTA, road traffic accident; CVE, cerebrovascular episode; AIDS, acquired immunodeficiency syndrome; RF, renal failure; ALD, alcoholic liver disease

TB was the leading UC as well as CC of deaths acros sall age groups, equally distributed across both genders. Jaundice was the second leading CoD followed by heart diseases and diarrhoeal diseases. Heart diseases, jaundice, homicide, alcohol intoxication, tetanus, drowning, snakebite and alcohol liver diseases were more common in males. Suicide and road traffic accidents (RTAs) were significantly more common in males than females (P=0.046 and 0.018, respectively). Deaths due to tetanus in Melghat were significantly higher (7.75 per 100000 population per year) as compared to the rest of India (1.12 per 100,000 UI) and equal to the highly impoverished countries such as south Sudan (7.62 per 100,000 UI)17. Out of total deaths, 50 per cent of deaths are due to preventable infections. Deaths due to TB were also higher in Melghat than rest of the India.

Table IV and Figure 2 provides the seasonal pattern of major UCs of death during the three periods. During the period 2011-2015, the proportion of deaths due to TB and jaundice was significantly higher in the winter and summer seasons as compared to the rainy season. Further, the deaths due to TB were significantly higher in winter as compared to other seasons (P<0.001) and the deaths due to diarrhoeal diseases were significantly higher in the rainy season as compared to other seasons (P=0.013). The proportion of CNS infection was also significantly higher in the rainy season as compared to other seasons (P=0.002) and deaths due to heart diseases were significantly higher during the summer season (P=0.044). Chronic obstructive airway disease (COAD) was higher during the monsoon.

Table IV Seasonal pattern of major underlying causes of death during the three periods
Causes of deaths 2004-2010 2011-2015 2016-2020 2004-2020 Deaths/100,000 population per yr
Rain (n=104), n (%) Winter (n=98), n (%) Summer (n=91), n (%) Rain (n=151), n (%) Winter (n=115), n (%) Summer (n=98), n (%) Rain (n=32), n (%) Winter (n=35), n (%) Summer (n=39), n (%) Rain Winter Summer Rain Winter Summer
TB 16 (15.3) 22 (22.4) 15 (16.5) 9 (5.9) 29 (25.2)*** 25 (25.5)*** 6 (18.8) 7 (20) 6 (15.4) 31 58 46 32.77 61.30*** 48.62
Diarrhoeal diseases 13 (12.5) 6 (6.1) 7 (7.7) 12 (7.9) 5 (4.4) 1 (1) 4 (12.5) 1 (2.9) 2 (5.1) 29 12 10 30.65** 12.68 10.57
Heart disease 10 (9.6) 11 (11.2) 11 (12.1) 7 (4.6) 12 (10.4) 12 (12.2) 2 (6.3) 2 (5.7) 7 (17.9) 19 25 30 20.08 26.42 31.71*
CNS infection 9 (8.6) 6 (6.1) 4 (4.4) 21 (13.9)*** 5 (4.4) 2 (2) 0 0 2 (5.1) 30 11 8 31.71** 11.63 8.46
Jaundice 7 (6.7) 4 (4.1) 8 (8.8) 3 (1.9) 14 (12.2)** 8 (8.2)** 3 (9.4) 1 (2.9) 0 13 19 16 13.74 20.08 16.91
COAD 5 (4.8) 4 (4.1) 2 (2.1) 11 (7.3)** 1 (0.9) 2 (2) 0 4 (11.4) 3 (7.7) 16 9 7 16.91 9.51 7.4
Cancer 3 (2.9) 4 (3.1) 5 (5.5) 2 (1.3) 6 (5.2) 7 (7.1) 1 (3.1) 4 (11.4) 2 (5.1) 6 14 14 6.34 14.8 14.8
Tetanus 2 (1.9) 2 (2) 0 2 (1.3) 2 (1.7) 1 (1) 0 1 (2.9) 1 (2.6) 4 5 2 4.23 5.28 2.11

*Obtained using Pearson’s Chi-square test. Rain; rainy season. TB, tuberculosis; CNS, central nervous system; COAD, chronic obstructive airway disease

Seasonal variation of causes of deaths during the study period (2004-2020). CNS, central nervous system; COAD, chronic obstructive airway disease
Fig. 2
Seasonal variation of causes of deaths during the study period (2004-2020). CNS, central nervous system; COAD, chronic obstructive airway disease

Discussion

In this study, the deaths in EPAGP were found to be higher than the national average. Health outcomes in this population have been reported to be poor because of poverty, low heath literacy, inaccessible and grossly inadequate healthcare services, low health seeking behaviour18, poor hygiene19 and high prevalence of addiction20.

A high rate of premature adult mortality is reported as a major issue at the population level as it creates a negative impact on families and communities21. CoD across EPAGP in India and worldwide shows respiratory infections, diarrhoeal diseases and non-communicable diseases as the major CoD1,3,22, a similar trend was also observed in Melghat.

In the present study, TB was found to be the most common underlying CoD across all age groups indicating shortfalls in outreach of the existing TB control programme and the need for extensive revision of such programmes suitable for the tribal areas. The prevalence of TB is high in the tribal area of Melghat (>0.4%), twice as compared to the national average due to low health literacy, crowded living conditions, delayed diagnosis, high prevalence of smoking and malnutrition, inaccessible health facilities and poverty23,24. Jaundice was reportedly the second most common UC across all age groups. This could be due to abuse of single use unsterile injections to multiple patients25 by unlicensed healthcare providers, multiple sexual partners26 drinking impure water22 and blood transfusion without testing for hepatitis virus27. Heart and diarrhoeal diseases were the third and fourth leading CoD. High diarrhoeal mortality is because of impure drinking water (90%) and impure food, inadequate hand hygiene and a high prevalence of malnutrition (body mass index<18.5)28. Intensive vaccination can prevent many deaths due to infections.

Heart diseases were the second leading CoD in the age group of 41-60 yr. The shift from infectious to non-communicable diseases in the adult age group shows the epidemiological transition in India29. The risk factors for heart diseases in Melghat are high tobacco and alcohol use, high prevalence of hypertension (10% in EPAGP), low birth weight (43%)30,31 and severe malnutrition in the age group of 0-5 yr (20%)30. Suicide is the sixth most common UC CoD mainly seen in 16-40 yr’ group indicating significant mental health issues in younger population warranting attention32. Many of the suicides were under the influence of alcohol or due to family disputes. Depression and anxiety may go unnoticed in the tribal areas in the context of limited family support. The greatest burden of suicide is seen in young people in developing countries33.

The probable causes of significantly high death rate in males in the present study were high risk behaviour of males e.g., smoking, alcoholism, more outdoor activities, occupational hazards and mental health issues, etc. These findings are in coraboration with other studies7. In the present study, jaundice deaths were more frequent in males due to more high risk behaviour e.g., multiple sex partners, alcoholism (50%), drinking impure water because of more frequent outdoor activities similar to previous reports4,7. Diarrhoeal deaths were more common among males, because of more outdoor work particularly due to consumption of impure outdoor water and impure food, and lesser tendency for handwashing with soap. Similar findings have been found in other low-income settings, such as in Gaza, where the prevalence of diarrhoea is reportedly higher in males (5.4/100) as compared to females (1.3/100)34. On the other hand in Melghat death due to heart diseases (coronary artery disease) are reportedly more common in males due to the higher prevalence of smoking, alcoholism and hypertension20.

In the present study, suicide deaths were more common in males than females similar to previous reports, indicating significantly more personal/social reasons and mental disorderin males35. Many suicides in Melghat were recorded as under the influence of alcohol. In present study, COAD (chronic obstructive airway disease) or COPD (chronic obstructive pulmonary disease) deaths were more common in males due to more smoking and outdoor pollution. RTA as CoD was significantly more in males than females. Motorbikes are the important mode of transport in Melghat due to inadequate public transport. Driving motorbikes, especially under the influence of alcohol is significantly higher amongst the tribal males. Similar findings were found in Iran36.

In the present study, significantly higher deaths occurred during the rainy season. The difference in the proportion of deaths across season was significant (P=0.002). It is because of more deaths due to diarrhoeal diseases, CNS infections and COAD during the rainy season. This highlights that the onset of rainy season opens the door to various infections and diseases due to unhygienic conditions. Poor transport connectivity during this season further inhibits access to hospitals. In the present study, TB deaths were found to be maximum in the winter season in Melghat when the temperature reaches to 2°C and people live in enclosed huts without proper ventilation leading to a greater risk of TB exposure. It is in contrast to the majority of studies (n=49), where TB decreased during winter24. In present study, diarrhoeal deaths were significantly more common during the rainy season, similar to previous studies37. It is because of more impure drinking water and more flies infecting food during the rainy season. There is no system for water purification and control of flies in Melghat. Open defecation (>90%) exacerbates more contamination of water and contamination by flies (unpublished data). Deaths due to CNS infections were more common in Melghat during the rainy season because of unhygienic surroundings in villages, poor drainage systems and water logging leading to mosquito breeding and more cerebral malaria/viral encephalitis, similar to the findings from a rural hospital in Uganda38.

In our study, COAD was more common during the rainy season with increased morbidity and mortality, due to the increased prevalence of respiratory viral infections6.

We used these CoD by VA to plan cluster randomized control trial (CRCT) to reduce ASMR. Our CRCT resulted in significant reduction in ASMR in intervention villages as compared to control villages (P<0.001), demonstrating the reliability of VA. Accurate information of CoD is essential for health policy, planning, monitoring, evaluation, comparisons, public attention and reducing premature deaths39.

This study was not without limitations. The study team chose to use the physician-reviewer method for diagnosis. Diagnosis of TB was not made by bacteriological confirmation. The accuracy of VA to know the CoDs was 75 per cent. This was a long-term follow up study of 16 yr. During the study, the interviewers were changed and the quality of data obtained could have been affected due to the poor educational status of responders. Furthermore, some villages were dropped out of the study and new villages were added in between the tenure. This may have limited the interpretation of trends in CoD over time.

Overall, our data showed that communicable diseases are the major CoDs (59.18%) in EPAGP. Providing oral rehydration solution (ORS) to all diarrhoea cases can save many lives immediately. Improving access to TB diagnosis and treatment services and ensuring treatment adherence can break the chain of transmission and prevent unnecessary deaths due to TB. It is essential to strengthen the routine death registration systems to cover all the locations and population groups across India.

As per our study finding from 2004 to 2021, the mortality rate in EPAGP among tribals in Melghat is more than 400 per 100,000 population of that age group per year. If we extrapolate our findings to all tribal areas of India, then, more than 208,846 people of EPAGP are dying every year40.

Financial support and sponsorship

The study was funded by Stichting Geron, Caring Friends, Mastek Foundation and the Tribal Development Department. The funders of the study had no role in study design, data collection, data analysis, data interpretation or writing of the report. The corresponding author had full access to all the data and had final responsibility to submit for the publication.

Conflicts of interest

None.

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Annexures

Annexure 1: Algorithm for respiratory diseases (pneumonia, TB and COPD) in verbal autopsy format.

II) Respiratory system disorder:

  • 1.

    Did the patient has cough?

     Yes ( ) No ( ) Don’t know ( )

  • 2.

    Was the patient breathless? Was there any difficulty in breathing?

     Yes ( ) No ( ) Don’t know ( )

If both answers are no, then skip subquestions 3 to 7 of question II and move to question III. But if one or both answers are yes, then continue the subquestions 3 to 7 of question II.

  • 3.

    Since how long patient had the cough? _______

    E (more than 24 hours)

  • 4.

    Was red expectoration seen in cough?

    C Yes ( ) No ( ) Don’t know ( )

  • 5.

    Since when was the shortness of breath? ------------- ,

    C (more than 6 hours)

  • 6.

    Was there a fever?

    S Yes ( ) No ( ) Don’t know ( )

  • 7.

    Was there any chest wall indrawing?

    C Yes ( ) No ( ) Don’t know ( )

  • 8.

    Was there chest pain?

    S Yes ( ) No ( )

     Don’t know ( ) Did chest pain increased with deep inspiration or breathing?

    C Yes ( ) No ( ) Don’t know ( )

If the symptoms (cough or fever) of sub questions 3 to 6 from question II, lasted for more than 15 days, then ask sub questions 9 to 25 of question II. If not, then go to question III)

  • 9.

    Since when the patient had cough ? --------

    E Yes (if more than 15 days, then 1E) ( ) No ( ) Don’t know ( )

  • 10.

    Was there blood in the cough?

    C Yes ( ) No ( ) Don’t know ( )

  • 11.

    Was there history of weight loss? (significant during last 15 days or more)

    E Yes ( ) No ( ) Don’t know ( )

  • 12.

    How was the patient’s health in the last 15 days?

    E Sick ( ) was good ( ) Don’t know ( )

  • 13.

    Was patient severely fatigued during last one month?

    S Yes ( ) No ( ) Don’t know ( )

  • 14.

    How was the appetite of the patient for the last 30 days before death?

    S Less ( ) good ( ) Don’t know ( )

  • 15.

    Did the patient had TB (tuberculosis)?

    S Yes ( ) No ( ) Don’t know ( )

  • 16.

    Did the patient come in contact with someone who had TB? (tuberculosis)

     S Yes ( ) No ( ) Don’t know ( )

  • 17.

    Was the patient administered TB vaccine (BCG)?

     Yes ( ) S No ( ) Don’t know ( )

  • 18.

    Was there any lump in the neck/armpit of the patient for more than 15 days?

    C Yes ( ) No ( ) don’t know ( )

  • 19.

    Did the patient had neck pain or headache and vomiting for more than 15 days?

     S Yes (----------------------) No ( ), don’t know ( ) ,

  • 20.

    Was there any change in the voice of patient, hoarseness and difficulty in swallowing?

     S Yes (----------------------) No ( ), don’t know ( ) ,

  • 21.

    Was there any breathlessness / shortness of breath/ intercostal indrawing? And since when?

     C Yes (----------------------) No ( ), don’t know ( ),

(Note: If cough persists for more than 15 days, then there is a more probability of TB)

  • 22.

    Was there any history of breathlessness/ difficulty in breathing for a long time? (because of which he could not work.)

    E Yes (----------------------) No ( ), don’t know ( ) ,

  • 23.

    Was there any history of cough for a long time?

    E Yes (----------------------) No ( ), don’t know ( ) ,

  • 24.

    Did the patient sit day and night because of breathlessness? Was he not able to sleep in the supine position?

    C Yes (----------------------) No ( ), don’t know ( ) ,

  • 25.

    Did the patient had cough with white expectoration for at least two months every year, for three consecutive years?

    C Yes (----------------------) No ( ), don't know ( )

    Did the cough increase during cold/winter?

    C yes ---------------------- No ( ), don’t know ( )

    S yes -------------------- _ No ( ), don’t know ( )

  • 26.

    Did the patient’s lips, palms and soles turn blue/cyanosed ?

    C Yes (----------------------) No ( ), don’t know ( )

  • 27.

    Did the patient has frequent breathlessness?

    S Yes (----------------------) No ( ), don’t know ( )

  • 28.

    Was the patient addict to smoking chillum/Bidis/cigarettes?

    C Yes (----------------------) No ( ), don't know ( )

  • (Questions 22 to 28)

Annexure 2

Inference on causes of death Possible Most probable Disease code
1) Pneumonia
2) Tuberculosis
3) COAD
4) IHD
5) Dysentry
6) Chronic diarrhoea
7) Acute diarrhoea
8) Rabies
9) AIDS
10) Tetanus
11) Jaundice
12) CNS infection
13) CVE
14) Fever cause unknown
15) Anemia
16) Oral cancer/malignancy
17) Other
18 Cause not Known
Underlying Cause________________________________________________( )__________
Singnature:___________________________
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