A Comparison of Effects of Scalp Nerve Block and Local Anesthetic Infiltration on the Inflammatory Response, Hemodynamic Response, and Postoperative Pain in Patients undergoing Craniotomy for Cerebral Aneurysms: A Randomized Controlled Trial

DOI: https://doi.org/10.21203/rs.2.53/v3

Abstract

BACKGROUND: The purpose of this study was to compare the effects of scalp nerve block (SNB) and local anesthetic infiltration (LA) with 0.75% ropivacaine on postoperative inflammatory response, intraoperative hemodynamic response, and postoperative pain control in patients undergoing craniotomy. METHODS: Fifty-seven patients were admitted for elective craniotomy for surgical clipping of a cerebral aneurysm. They were randomly divided into three groups: Group S (SNB with 15 mL of 0.75% ropivacaine), group I (LA with 15 mL of 0.75% ropivacaine) and group C (that only received routine intravenous analgesia). Pro-inflammatory cytokine levels in plasma for 72 hrs postoperatively, hemodynamic response to skin incision, and postoperative pain intensity were measured. RESULTS:The SNB with 0.75% ropivacaine not only decreased IL-6 levels in plasma 6 hrs after craniotomy but also decreased plasma CRP levels and increased plasma IL-10 levels 12 and 24 hrs after surgery compared to LA and routine analgesia. There were significant increases in mean arterial pressure 2 and 5 mins after the incision and during dura opening in Groups I and C compared with Group S. Group S had lower postoperative pain intensity, longer duration before the first dose of oxycodone, less consumption of oxycodone and lower incidence of PONV through 48 hrs postoperatively than Groups I and C. CONCLUSION: Preoperative SNB attenuated inflammatory response to craniotomy for cerebral aneurysms, blunted the hemodynamic response to scalp incision, and controlled postoperative pain better than LA or routine analgesia.

Background

Kenya ranks 10th out of 22 high TB burden countries globally1. The high prevalence of HIV in Kenya1 2 is a major contributing factor to TB incidence. Siaya County in Western Kenya has a high burden of tuberculosis and HIV with a TB case notification rate of 400/100,0003 and HIV prevalence of 15.1%1.

Latent tuberculosis infection (LTBI) is the presence of Mycobacterium tuberculosis (MTB) in the body without signs and symptoms, or radiographic or bacteriologic evidence of tuberculosis (TB) disease4. One method to measure the trend of TB transmission is through repeated tuberculin surveys in order to estimate the trend of the prevalence of tuberculous infection and annual risk of tuberculous infection (ARTI). ARTI is used to measure the effectiveness of TB control programs. In addition, If TST conversion is a secondary endpoint for candidate vaccines preventing infection, ARTI estimates may also be used to inform the sample size of such trials.

Kenya has carried out several TST surveys to estimate the ARTI. These surveys were standardized by targeting primary school children aged 6-13 years and using the same TST technique 5-7. The surveys were conducted in randomly selected districts and weighted for the underlying population distribution based on the most recent census. The ARTI estimates for Siaya district (where our present study was conducted) were 0.36%, 1.10% and 1.45% for the surveys conducted in 1986-1990, 1994-1996 and 2004-2007 respectively with a mean age of 10 years in each sampled population indicating a rising ARTI over time5-7.

Bacillus Calmette-Guerin (BCG), the TB vaccine given at birth, has not been shown to reliably prevent pulmonary tuberculosis in adolescents8. Adolescents may be prime candidates to receive new more effective TB vaccines because they are entering an age of steeply rising TB rates 9. TB vaccine trials enrolling adolescents will need to measure efficacy using several endpoints, including TB disease incidence. Measuring the ARTI and the prevalence of infection in preparation for TB vaccine trials can give an indication of TB transmission in target communities. In this study, we aimed to estimate the annual risk of infection with MTB among 12–18 year olds. Some of the interim results of this study have previously been reported in an abstract at the Biennial infectious disease conference, Nairobi Hospital Convention Centre, Nairobi, Kenya, 2017.

Methods

Study design and sample size:

The study area, Karemo Division with a population of 85,000 people, part of Siaya County is under a continuous health and demographic surveillance system (HDSS)10. The HDSS collects biannual data using household surveys. In brief, the study area was divided into 17 clusters of approximately equal population size. The clusters were randomly selected to give each adolescent an equal probability of participation. Eight out of 17 clusters were used for enrolment. In each cluster, HDSS data was used to identify households with adolescents; parents at these households were then approached to have their children participate in the study. The survey was conducted as part of a study on TB prevalence and incidence which used a prospective observational cohort design enrolling adolescents aged 12-18 years11.

Study Procedures

Informed Consent and clinical interviews

Parental consent was obtained at home by study staff prior to inviting adolescents to a mobile field site where minor assent was obtained prior to study participation. During enrolment, standard social demographic data were collected including age, gender, school enrolment status, parental social economic status, parental mortality, recent migration, and urban or rural residence. In addition, several clinical characteristics were collected including history of immunization with BCG, history of tuberculosis, BCG scar (we used the presence of a scar to stratify BCG status), weight and height. Study procedures have been described in more detail elsewhere11. The study received ethical approval of the Kenya Medical Research Institute and the US Centres for Disease Control and Prevention.

Tuberculin skin test and HIV testing:

All enrolled adolescents were offered a tuberculin skin test (TST) for LTBI after they provided a clinical history and vital signs were recorded. The TST used 0.1 ml of tuberculin purified protein derivative (PPD) containing 5TU (tuberculin units) RT23 with Tween 80 (Statens Serum Institute, Copenhagen, Denmark) and was injected intradermally into the middle dorsal region of the right forearm using a disposable tuberculin syringe and G.26 needle. Adolescents were offered a TST after giving clinical history and getting vital signs recorded. Adolescents returned after 72 hours for the reading of their TST results. Late TST readings were allowed up to a maximum of 7 days. All adolescents were offered HIV counselling and testing during the TST reading day. Parental/ guardian consent and adolescent assent were obtained prior to conducting HIV testing. Adolescents identified with HIV were referred to HIV care and treatment services at the Patient Support Centre at the Siaya District Hospital or to the nearest accessible Patient Support Centre.

The TST cut off we used as evidence for LTBI was ≥10mm in adolescents that did not have HIV or whose HIV status was unknown and ≥5mm in adolescents with HIV 12.

Statistical Analysis

Statistical analysis was performed using SAS 9.2 (SAS Institute Inc., Cary, NC, US). A three point moving average was used on the TST induration data to look for digit preference by observing differences in peaks between actual and smoothed data. The point prevalence of LTBI and 95% confidence intervals were calculated using survey procedures in SAS and adjusted for clustering. The prevalence of LTBI was estimated using the cut-off method and mirror method13. The cut-off method used the study defined cut-off of 10mm. In the mirror method, the mode of the distribution of those with presumed tuberculous infection is derived from the overall frequency distribution of TST reactions among the adolescents. Then, the total number of adolescents with positive TST reactions was estimated as the sum of the number of adolescents showing reaction sizes equal to the mode and double the number of adolescents with reaction sizes larger than the mode13. Bivariate analysis was used to determine significant associations between various risk factors and a positive tuberculin skin test. Factors significant at the p<0.2 level were further explored in a multivariate model using logistic regression. ARTI was calculated with the formula ARTI=1-(1-prevalence of infection) 1/mean age14..

Results

A total of 5004 adolescents aged 12-18 years were enrolled between August 2008 and August 2009. All adolescents enrolled received tuberculin skin tests (TST) and a total of 4808 (96.0%) came for their TST readings and were included in the analysis. Of the 4808 with TST readings, the mean age was 14.4 (SD 1.9), 2327 (48%) were female, the mean body mass index (BMI) was 17.9 (SD 2.5), 4518 (94%) were currently enrolled in school, 4550 (95%) lived in a rural area, 1289 (26.8%) were orphaned, 861 (18%) had no BCG scar, 23(0.5%) were HIV positive, and 21(0.4%) gave a history of previous tuberculosis (table 1). There was no significant difference in the baseline characteristics between those who came back for TST readings and those that failed to turn up [data not shown].

TST indurations

Of the 4808 adolescents with TST results, 4166 (86.7%) were read within 4 days, 2762 (58%) did not have any induration. Of the 3947 adolescents with a BCG scar, 2177 (55%) no induration compared to 585/861 (86%) of adolescents without a BCG scar. Among adolescents with TST reactivity, the mean TST induration was 13.2 mm (SD 5.4). There was marked digit preference at 10 mm, 15 and 16 mm and some digit avoidance at 13 mm (Figure 1). The smoothed data (three-point moving average) of all the adolescents showed a mode of 17 (Figure 1). Smoothed data for adolescents with and without a BCG scar showed a mode of 17 and 18 respectively (Figure 1).

Prevalence of infection and ARTI

Using the cut-off method, including one adolescent with HIV with a TST of 5mm, the overall prevalence of LTBI was 1544/4808 (32.1%, 95% CI 29.2-35.1) with a corresponding ARTI of 2.6% (95% CI 2.2-3.1). Among adolescents with a BCG scar, the prevalence of positive reactions was 33.5% (95% CI 30.3-36.8) with an estimated ARTI of 2.7% (95% CI 2.2-3.2) and among adolescents without a BCG scar, the prevalence of positive reactions was 25.6% (95% CI 22.0-29.2) and the corresponding ARTI 2.1% (95% CI 1.1-3.1) (Table 2). The Mirror method suggested an ARTI of 2.2% (95% CI 1.7-2.7) in those with and 2.1% (95% CI 1.1-3.1) for those without a BCG scar.

Risk factors for Tuberculous Infection (LTBI)

Using the cut-off method, risk factors for a positive TST result were being male (OR 1.3, 95%CI 1.2,1.5), history of having a household TB contact (OR 1.5, 95%CI 1.2,1.8), having a BCG scar (OR 1.5,95%CI 1.2,1.7) living in a rural area (OR 1.4, 95%CI 1.1,1.9), and being out of school (OR 1.8, 95%CI 1.4,2.3). The mirror method identified being male (OR 1.4, 95% CI 1.2,1.7) and having a household TB contact (OR 1.6, 95%CI 1.2,2.1) as risk factors for a positive TST (Table 3).

All risk factors identified during bivariate analysis remained independently associated with a positive TST in multivariate analysis (Table 3).

Discussion

Our study showed an ARTI of 2.6% (95% CI 2.2-3.1) with the cut-off method and 2.2% (95% CI 1.8-2.6) with the mirror method, both of which are more than double the expected based on serial TST surveys among children aged 10 years in the same area that reported an ARTI of 1.1% 5-7. This suggests that TB transmission may be more intense among adolescents than among young children. This is consistent with findings by Dodd et al who suggested estimates of TB infection based on surveys in children may underestimate infection incidence in adults15. A higher risk of infection among adolescents than among children of primary school age has also been reported elsewhere 16 17.

There are methodological challenges to measuring ARTI in adolescents, including the influence of previous BCG vaccination and exposure to environmental mycobacteria on TST results18, 19. Even though TST is a relatively inexpensive test, it has low specificity causing false positives in patients with history of BCG vaccination and environmental mycobacteria exposure20. In this study, BCG vaccination status was indeed associated with a positive TST result in the cut-off method, but the mirror method appeared to have eliminated this bias. ARTI was high both in those with and without a BCG scar, using either the cut-off or mirror method. Exposure to environmental mycobacteria appears not to have been a major factor given the low frequency of intermediate reactions (5-9 mm) and the similar prevalence estimate using the cut-off method and mirror method in those without BCG vaccination scar.

Risk factors for a positive TST were similar to those reported in studies elsewhere, including male sex9 and having a BCG scar21. The higher risk of TB infection in males might be related to older boys having more contact with adult men among whom TB prevalence is higher, as suggested by Dodd15. Although only a small proportion (6%) of adolescents in this study were not currently enrolled in school, they were significantly more likely to have a positive TST compared to in school youth 45% and 31% respectively (OR 1.8, 95%CI 1.1, 2.9). However, this subgroup may be a good target population for intensified case finding and prevention. The majority of adolescents enrolled were of rural residence (94.6%) and this was associated with a positive TST also in a multivariate model. However, the difference was not large (32% versus 27%). As expected history of a household contact was strongly predictive of a positive TST 40.1% versus 31.4%). Previous TB surprisingly was not associated with a positive TST, but numbers were small. Having both parents deceased was associated with a positive TST (34% versus 31%)). The study area has a high HIV prevalence of 15.1%% 2 and many deaths among parents are likely to have been due to HIV/AIDS, which in this area is strongly associated with tuberculosis indicating a higher risk of LTBI in orphaned children before their parents died.

The ARTI estimates are derived from a point prevalence estimate and repeated TST surveys would need to be conducted to see how this correlates with the incidence of infection and age associated risks of infection16, 17. While BCG had some influence on TST reading results using the cut-off method, this was no longer the case using the mirror method. Digit preference was corrected by smoothing, though might be further reduced in the future by further strengthening training and supervision.

Preventing TB disease instead of infection has been the key goal of vaccine development 22. Epidemiological and mathematical modelling studies have shown a pre-infection vaccine would have a high level impact on TB disease control22. A pre-infection vaccine will require choice of an age range where the risk of infection rises but before majority of the age group becomes infected. Adolescents are an important group for vaccination against TB because while TB incidence is relatively low in the age group 5-14 years, it rises rapidly in adolescence23. In our study majority of adolescents (67.9%) were TST negative indicating this would be a good age group to target for prevention of infection vaccine studies. We have reported on the incidence of tuberculosis in adolescents elsewhere24. The incidence of TB addresses the sample sizes needed for TB vaccine efficacy trials preventing disease; whether primary disease or reactivation from previous TB infection. Because of difficulties in having a human challenge model with tuberculosis a pathway to understanding the immune mechanisms of protection against tuberculosis with new vaccines would be to conduct prevention of infection with M.tuberculosis studies as a marker of biologic impact22. Since infection with M.tuberculosis happens much more often than TB disease, the trials will be much smaller and trial results would be obtained much sooner allowing a read-out on a TB vaccine candidate’s likely efficacy before doing larger scale efficacy studies.

We conclude that the high TB transmission rates we found in this study, suggest that adolescents in this region may be an appropriate target group for TB vaccine trials including TB vaccine trials aiming to prevent infection.

Abbreviations

TB Tuberculosis

POI Prevention of infection

BCG Bacille Calmette-Guerin

TST Tuberculin skin test

HIV Human immunodeficiency virus

ARTI Annual Risk of tuberculous infection

LTBI Latent tuberculosis infection

MTB Mycobacterium tuberculosis

HDSS health and demographic surveillance system

PPD Purified protein derivative

TU Tuberculin units

Declarations

Ethics approval and consent to participate

The protocol and informed consent forms were reviewed and approved by the KEMRI local and national scientific steering committees and the KEMRI national ethical review committee and the Institutional Review Boards (IRBs) of CDC and the AERAS Global TB Vaccine Foundation. Parental consent was obtained at home by study staff prior to inviting adolescents to a mobile field site where minor assent was obtained prior to study participation

Consent for publication

Not applicable

Availability of data and material

The data supporting the findings of this study have been included as an additional supporting file in the submission.

Competing interests

KNCV tuberculosis foundation provided some funding for the project and participated in Manuscript preparation. The other funding agencies did not participate in data analysis or the preparation of this manuscript or in the decision to submit the manuscript for publication. The authors have no conflicts of interest relevant to this article to disclose.

Role of funder

This study was supported by grants from: The European and Developing Countries Clinical Trials Partnership (grant number: IP_07_32080_003), Aeras Global TB Vaccine Foundation, KNCV TB Foundation, Netherlands Organisation for Scientific Research (NACCAP), Vienna School of Clinical Research, San Rafaele Laboratory, Milan Italy.

Authors' contributions

VN wrote the protocol, conducted the study, analysed and interpreted the data and wrote the manuscript. AB participated in data analysis and manuscript development. AH, EM, KL and MB participated in developing the protocol, reviewed data and multiple versions of the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We would like to acknowledge the Director KEMRI for approval of this manuscript and KEMRI/CDC. KEMRI/CDC is a member of the INDEPTH Network. We also acknowledge the dedicated staff especially recruitment staff and village reporters that made it possible to contact all potential study participants. Some of the interim results of this study have previously been reported in an abstract at the Biennial infectious disease conference, Nairobi Hospital Convention Centre, Nairobi, Kenya, 2017

Disclaimer

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

References

1.Kenya AIDS indicator survey (KAIS). 2012.(Accessed December, 15 2017)

2.statistics KNBO. Kenya Demographic And Heath Survey 2008-2009. 2010. (Accessed December, 15 2017)

3.Kenya national leprosy and tuberculosis program report http://www.nltp.co.ke/docs/Annual_Report_2009.pdf . 2009. (Accessed December, 15 2017)

4.CDC. Latent Tuberculosis Infection: A Guide for Primary Health Care Providers. https://www.cdc.gov/tb/publications/ltbi/pdf/targetedltbi.pdf . 2013. (Accessed December, 15 2017)

5.Odhiambo JA, Borgdorff MW, Kiambih FM, et al. Tuberculosis and the HIV epidemic: increasing annual risk of tuberculous infection in Kenya, 1986-1996. Am J Public Health. Jul 1999;89(7):1078-1082.

6.Kwamanga D, Chakaya J, Sitienei J, Kalisvaart N, L'Herminez R, van der Werf MJ. Tuberculosis transmission in Kenya: results of the third National Tuberculin Survey. Int J Tuberc Lung Dis. 2010; Jun;14(6):695-700.

7.Bosman MC, Swai OB, Kwamanga DO, Agwanda R, Idukitta G, Misljenovic O. National tuberculin survey of Kenya, 1986-1990. Int J Tuberc Lung Dis. Apr 1998;2(4):272-280.

8.Colditz GA, Brewer TF, Berkey CS, et al. Efficacy of BCG vaccine in the prevention of tuberculosis. Meta-analysis of the published literature. Jama. Mar 2 1994;271(9):698-702.

9.Mahomed H, Hawkridge T, Verver S, et al. Predictive factors for latent tuberculosis infection among adolescents in a high-burden area in South Africa. Int J Tuberc Lung Dis. 2011; Mar;15(3):331-336.

10.Odhiambo FO, Laserson KF, Sewe M, et al. Profile: the KEMRI/CDC Health and Demographic Surveillance System--Western Kenya. Int J Epidemiol. Aug;41(4):977-987.

11.Nduba V, Hoog AH, Mitchell E, Onyango P, Laserson K, Borgdorff M. Prevalence of tuberculosis in adolescents, western Kenya: implications for control programs. Int J Infect Dis. 2012; Jun;35:11-17.

12.(CDC) CfDCaP. Targeted Tuberculin Testing and Treatment of Latent Tuberculosis Infection. MMWR. Morbidity and Mortality Weekly Reports; Retrieved from http://www.cdc.gov/mmwr/PDF/rr/rr4906.pdf . 2000, June 9;49 (No. RR-6).

13.Rieder HL. Methodological issues in the estimation of the tuberculosis problem from tuberculin surveys. Tuber Lung Dis. Apr 1995;76(2):114-121.

14.Adetifa IM, Muhammad AK, Jeffries D, et al. A Tuberculin Skin Test Survey and the Annual Risk of Mycobacterium tuberculosis Infection in Gambian School Children. PLoS One. 2015; 10(10):e0139354.

15.Dodd PJ, Looker C, Plumb ID, et al. Age- and Sex-Specific Social Contact Patterns and Incidence of Mycobacterium tuberculosis Infection. Am J Epidemiol. 2016; Jan 15;183(2):156-166.

16.Sutherland I, Fayers PM. The association of the risk of tuberculous infection with age. Bull Int Union Tuberc. 1975;50(1):70-81.

17.Nagelkerke N, Heisterkamp S, Borgdorff M, Broekmans J, Van Houwelingen H. Semi-parametric estimation of age-time specific infection incidence from serial prevalence data. Stat Med. Feb 15 1999;18(3):307-320.

18.Rieder H. Annual risk of infection with Mycobacterium tuberculosis. Eur Respir J. Jan 2005;25(1):181-185.

19.Fine PE, Ponnighaus JM, Maine N. The distribution and implications of BCG scars in northern Malawi. Bull World Health Organ. 1989;67(1):35-42.

20.Chapman HJ, Lauzardo M. Advances in diagnosis and treatment of latent tuberculosis infection. J Am Board Fam Med. 2014; Sep-Oct;27(5):704-712.

21.Farhat M, Greenaway C, Pai M, Menzies D. False-positive tuberculin skin tests: what is the absolute effect of BCG and non-tuberculous mycobacteria? Int J Tuberc Lung Dis. Nov 2006;10(11):1192-1204.

22.Hawn TR, Day TA, Scriba TJ, et al. Tuberculosis vaccines and prevention of infection. Microbiol Mol Biol Rev. Dec 2014;78(4):650-671.

23.Marais BJ, Donald PR, Gie RP, Schaaf HS, Beyers N. Diversity of disease in childhood pulmonary tuberculosis. Ann Trop Paediatr. Jun 2005;25(2):79-86.

24.Videlis Nduba M, MPH, Anna H. Van’t Hoog, MD, Msc, PhD, Ellen M.H. Mitchell, PhD , Martien Borgdorff, MD, PhD , Kayla F. Laserson, ScD Incidence of pulmonary tuberculosis and cohort retention among adolescents in Western Kenya. Submitted. 2016.

Tables

Table 1: Demographic characteristics of 4808 adolescents undergoing tuberculin skin testing in Kenya, 2008-2009.

Characteristic

Category

All (4808)

Tuberculin skin test (TST)

Reactive

1544 (32.1%)

Non reactive

3264 (67.9%)

Gender

Female

2327 (48.4%)

Male

2481 (51.6%)

School going

Yes

4518 (94.0%)

No

290 (6.0%)

HIV status

Positive

23 (0.5%)

Negative

1985 (41.3%)

Unknown

2165 (45.0%)

Residence

Rural

4550 (94.6%)

Urban

258 (5.4%%)

Previous TB

Yes

21 (0.4%)

No

4787 (99.6%)

History of TB contact

Yes

138 (2.9%)

No

4670 (97.1%)

Deceased parents

One parent deceased or both alive

3519 (73.2%)

Both deceased

1289 (26.8%)

Socio economic status

Upper class

1582 (32.9%)

Middle class

1636 (34.0%)

Lower class

1590 (33.1%)

Table 2: ARTI estimates and prevalence of infection presented for all adolescents, those with and without a BCG scar

 

N

Mean age (years)

≥10mm

 

*Mirror method 17 mm

 

 

 

P

ARTI

CI (95%)

P

ARTIπ

CI (95%)

All

4808

14.4

32.1%

2.6%

(2.2,3.1)

27.6%

2.2%

(1.8,2.6)

BCG scar

3947

14.4

33.5%

2.7%

(2.2,3.2)

27.8%

2.2%

(1.7,2.7)

BCG scar absent

859

14.2

25.6%

2.1%

(1.1,3.1)

27.0%

2.1 %

(1.1,3.1)

*The total number of adolescents with true reactions was calculated by adding the number of adolescents showing reaction sizes equal to the mode to double the number with reaction sizes larger than the mode to determine the numerator

The Cut-off for HIV+ was ≥5mm

π ARTI formula =1-(1-prevalence of infection) 1/mean age

CI 95% Confidence interval

Table 3: Risk factors for a positive tuberculin skin test (TST) for the 10mm cut-off method and the 17mm mirror method

Risk Factor

Tuberculin skin test >=10mm n=4808

Multivariate

Tuberculin skin test >=17mm n=4808

Multivariate

 

 

Negative

Positive

OR, 95% CI

OR, 95% CI

Negative

Positive

OR, 95% CI

OR, 95% CI

Gender

Female

1650

677/2327 (29.1%)

1

2076

251/2327 (10.8%)

1

 

 

Male

1614

867/2481 (34.9%)

1.3(1.2,1.5)

1.3 (1.2,1.5)

2129

352/2481 (14.2%)

1.4 (1.2,1.6)

1.4 (1.2,1.7)

History of a house hold TB contact

Yes

224

150/374 (40.1%)

1.5 (1.2,1.8)

 1.5(1.2,1.8)

119

19/138 (13.8%)

1

 

 

No

3040

1394/4434 (31.4%)

1

 

4086

584/4670 (12.5%)

1.6 (1.2,2.1)

 1.6(1.2,2.1)

Previous TB

Yes

15

6/21 (28.6%)

1

 

18

3/21 (14.3%)

1

 

 

No

3232

1528/4787 (32.1%)

0.8 (0.3,2.1)

 

4163

597/4760 (12.5%)

1.2 (0.4,3.7)

 

BCG Scar

Yes

2623

1324/3947 (33.5%)

1.3 (1.2,1.7)

1.5 (1.3,1.8)

3450

497/3947 (12.6%)

1.0 (0.8,1.3)

 1.0 (0.8,1.3)

 

No

641

220/861 (25.6%)

1

 

753

106/859 (12.3%)

1

 

Residence

Urban

189

69/258 (26.7%)

1

 

231

27/258 (10.5%)

1

 

 

Rural

3075

1475/4550 (32.4%)

1.2 (1.0,1.5)

1.4 (1.1,1.9) 

3974

576/4550 (12.7%)

1.2 (0.8,1.9)

 1.2(0.8,1.9)

School going

Yes

3103

1415/4518 (31.3%)

1

 

3960

558/4518 (12.4%)

1

 

 

No

161

129/290 (44.5%)

1.8(1.4,2.2)

1.8 (1.4,2.3)

245

45/290 (15.5%)

1.3 (0.9,1.8)

 1.3(1.0,1.8)

Orphaned

Yes

1136

585/1721 (34.0%)

1

1474

247/1721 (14.4%)

 1

 

 

No

2128

959/3087 (31.1%)

1.1 (1.0,1.3)

1.1(1.0,1.3) 

2731

356/3087 (11.5%)

1.3 (1.1,1.5)

 1.3(1.1,1.5)