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Gender Difference in Use of Insecticide Treated Nets After a Universal Free Distribution Campaign in Kano State in Nigeria
                                                                                                        Ashley Garley1, Elizabeth Ivanovich1, Erin Eckert2, Svetlana Negroustoueva3, Yazoume Ye1
                                                                                                           1
                                                                                                            ICF International, 2US Agency for International Development, 3Independent Consultant

                                                                                            Background
                                                                                            Although malaria affects men and women, their vulnerability and access to treatment is influenced by gender roles and affected by equity in society. A recent shift in
                                                                                            insecticide treated net (ITN) distribution strategy from targeting pregnant women and children under five to aiming for universal coverage among the general population,
                                                                                            raises issues associated with equity of access and equality in the use of ITN. There is a need for analysis to assess the effects of gender on the uptake of this key intervention
                                                                                            for malaria control. The recent post-campaign survey in Northern Nigeria offers an opportunity to examine gender differences in ITN use, by using sex-disaggregated data.
                                                                                                             Realities in Nigeria:                                            Current ITN distribution strategy in Nigeria :
                                                                                                             Low ITN coverage                                                 Mass ITN distribution campaigns for all population groups increase ITN coverage
                                                                                                             • 8% ITN ownership (DHS 2008)                                    •63 million new Long lasting Insecticide Treated Net (LLIN) to be distributed
                                                                                                             • 6% ITN use among children under five years (DHS 2008)          by the end of 2010
  Photo source: Arne Hoel / World Bank                                                                       • 5% ITN use among pregnant women (DHS 2008)                     •At least 80% of LLINs distributed put in use
      Methods                                                                                               Sampling
      Location of the study site-Nigeria                                                                                                                                            Data Collection
                                                                                                            •Sample Size=4,602 individuals                                          •Household survey took place Oct 19 –Nov 4, 2009
                                                       Kano State                                           •Beta=80%, alpha=5%, design effect= 1.75                                •5 months after campaign 1
                                                                                                            •Accounting for non-response rate: 5%                                   •3 months after campaign 2
                                                                                                            •Average size of household=5 people                                     •Structured questionnaire was used
                                                                                                            •Children under 5 years=20% of population                               •Head of Household was primary respondent
                                                                                   Warawa
                                                                                                            •Pregnant females=3.5% of female population                             •Verbal informed consent obtained before interview
                                                                                                            •Power to detect 50% point change in household net ownership
                                                                                                                                                                                    Statistical Analysis
                                                                                                            Sampling Procedure                                                      •Analysis was restricted to only individuals living in households with at least 1 ITN (3,056)
                                                                                                            •Sampling frame: Questionnaire adapted from the                         •Descriptive Analysis-described gender difference in ITN use by background characteristics
                                                            Wave 1 May 2009
                                                                                                            Malaria Indicator Survey                                                •Logistic regression (binary response)-assessed ITN use difference between male and female
                                                            Wave 2 July 2009                                •Selection of 30 clusters - wards                                       controlling for several covariates (campaign Waves, age, place of residence, education of the
                                                                                                            •List of community-villages compiled in each ward                       head of households, polygamous households [yes/no] and ratio of ITNS to household
                                                                           Source: Ye et al, 2012           •Selection of 17 households per community                               members

Results
 Individual Living in Household with ITN                                                                          ITN Use                                                                                     Sex as a Predictor for ITN Use
                                                                                                                                                                                                                                               Number of        # individual using
  Table 1: Percentage of individuals living in households with ITNs by gender and background                                                                                                                   Factors                         individuals           ITN (%)            Odd Ratios (95% CI)    p value
                                                                                                                                                                                                               Total number of individuals        3,056             1622 (53.1)
  characteristics.
                                                                                                                                                                                                               Explanatory variable
  Background                             Female                     Male                       Total                                                                                                           Gender
  characteristic                                                                                                                                                                                                      Male                         1,494             729 (48.8)                     1
                                Percentage         N         Percentage        n      Percentage        N                                                                                                             Female                       1,562             893 (57.2)             1.46 (1.25-1.70)   0.000
                                                                                                                                                                                                               Covariates
  Total                             66.7          2,342         66.1       2,260            66.4       4,602                                                                                                   Wealth quintiles
                                                                                                                                                                                                                      Lowest                        521              273 (52.4)             0.80 (0.61-1.05)   0.104
  Campaign Waves                                                                                                                                                                                                      Second                        610              307 (50.3)             0.82 (0.64-1.06)   0.128
                                                                                                                                                                                                                      Third                         640              359 (56.1)             1.09 (0.86-1.39)   0.479
    Wave 1                          63.8          1,169         63.3       1,175            63.6       2,344                                                                                                          Fourth                        653              341 (52.2)             0.89 (0.70-1.13)   0.334
    Wave 2                          69.6          1,173         69.1       1,085            69.4       2,258                                                                                                          Highest                       632              342 (54.1)                     1
                                                                                                                                                                                                               Wave
  Place of residence                                                                                                                                                                                                  Wave 1                       1,490             735 (49.3)                     1
                                                                                                                                                                                                                      Wave 2                       1,566             887 (56.6)             1.38 (1.18-1.61)   0.000
    Urban                           69.5          791           68.5       774              69.0       1,565                                                                                                   Age
                                                                                                                                                                                                                      Under 5 year                  639              397 (62.1)             1.41 (1.14-1.75)   0.002
    Rural                           65.3          1,551         64.9       1,486            65.1       3,037
                                                                                                                                                                                                                      5-15 years                    971              471 (48.5)             0.88 (0.73-1.06)   0.169
  Wealth quintiles                                                                                                                                                                                                    15-25 years                   467              203 (43.5)             0.57 (0.45-0.73)   0.000
                                                                                                                                                                                                                      25 years and plus             979              551 (56.3)                     1
    Lowest                          62.3          453           65.7       364              64.0       817                                                                                                     Place of residence
                                                                                                                                                                                                                      Urban                        1080              538 (49.8)                     1
    Second                          70.0          466           71.4       398              70.7       864                                                                                                            Rural                        1976             1,084 (54.9)            1.15 (0.98-1.35)   0.098
    Middle                          69.3          452           66.2       494              67.7       946                                                                                                     Education head of household
                                                                                                                                                                                                                      None                         1,880             965 (51.3)                     1
    Fourth                          70.6          472           69.0       464              69.8       936                                                                                                            Primary                       636              374 (58.8)             1.38 (1.13-1.67)   0.001
                                                                                                                                                                                                                      Secondary                     382              185 (48.4)             0.87 (0.68-1.12)   0.288
    Highest                         61.7          499           60.0       540              60.9       1,039       Overall, ITN use among individuals living in households with at least one                          Higher                        115              75 (65.2)              1.80 (1.16-2.78)   0.009
                                                                                                                   ITN was 53%; however, there was a significant difference in use                                    Missing                       43
Of the 4,602 individuals in the survey samples, 66% lived in households                                            between females and males (57% vs. 53%, p<0000.1). Consistently,
                                                                                                                                                                                                               Polygamous household
                                                                                                                                                                                                                      Yes                          1,291             666 (51.6)                     1
which owned at least one ITN with no difference between females (67%)                                              females reported significantly higher ITN use than males in Wave 1 (52%
                                                                                                                                                                                                                      No                           1,765             956 (54.2)             0.88 (0.76-1.03)   0.114
                                                                                                                                                                                                               Ratio 1 net for 2 person met
and males (66%). The percentage of individuals living in households with                                           vs. 46%, p=0.017) and Wave 2 (62% vs. 51%, p<0.0001). Similar patterns                             No                           2,268            1,077 (47.5)                    1

at least one ITN increased by 5.8 points between Wave 1 (May 2009) and                                             were observed by residence. Furthermore, females had significantly
                                                                                                                                                                                                                      Yes                           788              545 (69.2)             2.53 (2.11-3.04)
                                                                                                                                                                                                               Model fit: LR chi2(18)=238.45; p value=0.0000; Pseudo R2=0.057; Log likelihood = -1963.54
                                                                                                                                                                                                                                                                                                               0.000

Wave 2 (July 2009) for both sexes . There was no difference by sex in the                                          higher use of ITNs compared to males when analyzed by household
proportion of individuals living in households which owned at least one                                                                                                                               Logistic regression showed females are more likely to use ITNs compared to males
                                                                                                                   wealth: quintiles except the second (53% vs 47%, p=0.147) and middle
ITN in either rural or urban areas. Individuals in the households in the                                                                                                                              after controlling for potential confounders, (OR:1.5, 95% CI: 1.3-1.7). Age showed a
                                                                                                                   (60% vs.53%, p=0.069).                                                             significant effect on ITN use; children under five had higher odds of using an ITN,
second and fourth wealth quintiles were the most likely to own at least
one ITN ( 71% and 70%, respectively).                                                                                                                                                                 while individuals age 15-25 years were less likely to use an ITN. Individuals living in
                                                                                                                                                                                                      households with a head that had no formal education were less likely to use an ITN.
                                                                                                                                                                                                      Individuals living in households with at least one ITN for every two members were 2.5
                                                                                                                                                                                                      times more likely to use an ITN compared to individuals living in households with less
                                                                                                                                                                                                      than one ITN for every two members.

      Conclusions                                                                                                                                                      Acknowledgments
       The results from this analysis in Kano state showed that household ITN ownership increased more than tenfold,                                                  This study was the result of a collective effort with several partners including USAID Nigeria, SuNMAP, Malaria Consortium,
       from 6% before to 71% after the campaigns. There was no significant difference between the proportion of                                                       RMS and MEASURE Evaluation. The authors would like to thank all the institutions and individuals who contributed to the
       females and males living in households with at least one ITN. However, a higher percentage of females used                                                     design and implementation of the post-campaign survey. In particular, the team would like to acknowledge Albert Killian, the
       ITNs compared to males , even after controlling for several covariates, females remained more likely to use                                                    Research Marketing Service (RMS) team. Special thanks to Emmanuel Adegbe and Olatunde Oladimeji from SuNMap for
                                                                                                                                                                      overseeing the field activities and data processing. The team is also grateful to all the people who reviewed and gave
       ITNs compared to males .                                                                                                                                       comments on the initial draft. This study was made possible by support from the U.S. Agency for International Development
       This study reveals gender disparity in ITN use, with men less likely to use ITNs . Notably, the uptake of the                                                  (USAID) under the terms of Cooperative Agreement GPO-A-00-03-00003-00. The opinions expressed are those of the authors
       intervention among the most-at-risk group (females) is higher than males. Further research is needed to                                                        and do not necessarily reflect the views of USAID, or the United States Government.
       identify whether gender disparities in ITN use is related to the traditional targeting of women with malaria
       interventions; however, results provide enough evidence to design gender-sensitive messaging for ITN
       distribution to ensure that males equally use ITNs.

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Gender Difference in Use of Insecticide Treated Nets After a Universal Free Distribution Campaign in Kano State in Nigeria

  • 1. Gender Difference in Use of Insecticide Treated Nets After a Universal Free Distribution Campaign in Kano State in Nigeria Ashley Garley1, Elizabeth Ivanovich1, Erin Eckert2, Svetlana Negroustoueva3, Yazoume Ye1 1 ICF International, 2US Agency for International Development, 3Independent Consultant Background Although malaria affects men and women, their vulnerability and access to treatment is influenced by gender roles and affected by equity in society. A recent shift in insecticide treated net (ITN) distribution strategy from targeting pregnant women and children under five to aiming for universal coverage among the general population, raises issues associated with equity of access and equality in the use of ITN. There is a need for analysis to assess the effects of gender on the uptake of this key intervention for malaria control. The recent post-campaign survey in Northern Nigeria offers an opportunity to examine gender differences in ITN use, by using sex-disaggregated data. Realities in Nigeria: Current ITN distribution strategy in Nigeria : Low ITN coverage Mass ITN distribution campaigns for all population groups increase ITN coverage • 8% ITN ownership (DHS 2008) •63 million new Long lasting Insecticide Treated Net (LLIN) to be distributed • 6% ITN use among children under five years (DHS 2008) by the end of 2010 Photo source: Arne Hoel / World Bank • 5% ITN use among pregnant women (DHS 2008) •At least 80% of LLINs distributed put in use Methods Sampling Location of the study site-Nigeria Data Collection •Sample Size=4,602 individuals •Household survey took place Oct 19 –Nov 4, 2009 Kano State •Beta=80%, alpha=5%, design effect= 1.75 •5 months after campaign 1 •Accounting for non-response rate: 5% •3 months after campaign 2 •Average size of household=5 people •Structured questionnaire was used •Children under 5 years=20% of population •Head of Household was primary respondent Warawa •Pregnant females=3.5% of female population •Verbal informed consent obtained before interview •Power to detect 50% point change in household net ownership Statistical Analysis Sampling Procedure •Analysis was restricted to only individuals living in households with at least 1 ITN (3,056) •Sampling frame: Questionnaire adapted from the •Descriptive Analysis-described gender difference in ITN use by background characteristics Wave 1 May 2009 Malaria Indicator Survey •Logistic regression (binary response)-assessed ITN use difference between male and female Wave 2 July 2009 •Selection of 30 clusters - wards controlling for several covariates (campaign Waves, age, place of residence, education of the •List of community-villages compiled in each ward head of households, polygamous households [yes/no] and ratio of ITNS to household Source: Ye et al, 2012 •Selection of 17 households per community members Results Individual Living in Household with ITN ITN Use Sex as a Predictor for ITN Use Number of # individual using Table 1: Percentage of individuals living in households with ITNs by gender and background Factors individuals ITN (%) Odd Ratios (95% CI) p value Total number of individuals 3,056 1622 (53.1) characteristics. Explanatory variable Background Female Male Total Gender characteristic Male 1,494 729 (48.8) 1 Percentage N Percentage n Percentage N Female 1,562 893 (57.2) 1.46 (1.25-1.70) 0.000 Covariates Total 66.7 2,342 66.1 2,260 66.4 4,602 Wealth quintiles Lowest 521 273 (52.4) 0.80 (0.61-1.05) 0.104 Campaign Waves Second 610 307 (50.3) 0.82 (0.64-1.06) 0.128 Third 640 359 (56.1) 1.09 (0.86-1.39) 0.479 Wave 1 63.8 1,169 63.3 1,175 63.6 2,344 Fourth 653 341 (52.2) 0.89 (0.70-1.13) 0.334 Wave 2 69.6 1,173 69.1 1,085 69.4 2,258 Highest 632 342 (54.1) 1 Wave Place of residence Wave 1 1,490 735 (49.3) 1 Wave 2 1,566 887 (56.6) 1.38 (1.18-1.61) 0.000 Urban 69.5 791 68.5 774 69.0 1,565 Age Under 5 year 639 397 (62.1) 1.41 (1.14-1.75) 0.002 Rural 65.3 1,551 64.9 1,486 65.1 3,037 5-15 years 971 471 (48.5) 0.88 (0.73-1.06) 0.169 Wealth quintiles 15-25 years 467 203 (43.5) 0.57 (0.45-0.73) 0.000 25 years and plus 979 551 (56.3) 1 Lowest 62.3 453 65.7 364 64.0 817 Place of residence Urban 1080 538 (49.8) 1 Second 70.0 466 71.4 398 70.7 864 Rural 1976 1,084 (54.9) 1.15 (0.98-1.35) 0.098 Middle 69.3 452 66.2 494 67.7 946 Education head of household None 1,880 965 (51.3) 1 Fourth 70.6 472 69.0 464 69.8 936 Primary 636 374 (58.8) 1.38 (1.13-1.67) 0.001 Secondary 382 185 (48.4) 0.87 (0.68-1.12) 0.288 Highest 61.7 499 60.0 540 60.9 1,039 Overall, ITN use among individuals living in households with at least one Higher 115 75 (65.2) 1.80 (1.16-2.78) 0.009 ITN was 53%; however, there was a significant difference in use Missing 43 Of the 4,602 individuals in the survey samples, 66% lived in households between females and males (57% vs. 53%, p<0000.1). Consistently, Polygamous household Yes 1,291 666 (51.6) 1 which owned at least one ITN with no difference between females (67%) females reported significantly higher ITN use than males in Wave 1 (52% No 1,765 956 (54.2) 0.88 (0.76-1.03) 0.114 Ratio 1 net for 2 person met and males (66%). The percentage of individuals living in households with vs. 46%, p=0.017) and Wave 2 (62% vs. 51%, p<0.0001). Similar patterns No 2,268 1,077 (47.5) 1 at least one ITN increased by 5.8 points between Wave 1 (May 2009) and were observed by residence. Furthermore, females had significantly Yes 788 545 (69.2) 2.53 (2.11-3.04) Model fit: LR chi2(18)=238.45; p value=0.0000; Pseudo R2=0.057; Log likelihood = -1963.54 0.000 Wave 2 (July 2009) for both sexes . There was no difference by sex in the higher use of ITNs compared to males when analyzed by household proportion of individuals living in households which owned at least one Logistic regression showed females are more likely to use ITNs compared to males wealth: quintiles except the second (53% vs 47%, p=0.147) and middle ITN in either rural or urban areas. Individuals in the households in the after controlling for potential confounders, (OR:1.5, 95% CI: 1.3-1.7). Age showed a (60% vs.53%, p=0.069). significant effect on ITN use; children under five had higher odds of using an ITN, second and fourth wealth quintiles were the most likely to own at least one ITN ( 71% and 70%, respectively). while individuals age 15-25 years were less likely to use an ITN. Individuals living in households with a head that had no formal education were less likely to use an ITN. Individuals living in households with at least one ITN for every two members were 2.5 times more likely to use an ITN compared to individuals living in households with less than one ITN for every two members. Conclusions Acknowledgments The results from this analysis in Kano state showed that household ITN ownership increased more than tenfold, This study was the result of a collective effort with several partners including USAID Nigeria, SuNMAP, Malaria Consortium, from 6% before to 71% after the campaigns. There was no significant difference between the proportion of RMS and MEASURE Evaluation. The authors would like to thank all the institutions and individuals who contributed to the females and males living in households with at least one ITN. However, a higher percentage of females used design and implementation of the post-campaign survey. In particular, the team would like to acknowledge Albert Killian, the ITNs compared to males , even after controlling for several covariates, females remained more likely to use Research Marketing Service (RMS) team. Special thanks to Emmanuel Adegbe and Olatunde Oladimeji from SuNMap for overseeing the field activities and data processing. The team is also grateful to all the people who reviewed and gave ITNs compared to males . comments on the initial draft. This study was made possible by support from the U.S. Agency for International Development This study reveals gender disparity in ITN use, with men less likely to use ITNs . Notably, the uptake of the (USAID) under the terms of Cooperative Agreement GPO-A-00-03-00003-00. The opinions expressed are those of the authors intervention among the most-at-risk group (females) is higher than males. Further research is needed to and do not necessarily reflect the views of USAID, or the United States Government. identify whether gender disparities in ITN use is related to the traditional targeting of women with malaria interventions; however, results provide enough evidence to design gender-sensitive messaging for ITN distribution to ensure that males equally use ITNs.