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Climate variability and the dichotomy in male–female school attendance:

a case study of Zamfara State in semi-arid Nigeria

Joseph O. AdejuwonDepartment of Water Resources Management and Agrometeorology, Federal University of Agriculture, Abeokuta, Nigeria

Introduction Climate variability is a global phenomenon that is not limited to any climatic region. Its associated impacts pose serious dan-ger to agriculture, international trade and school attendance. Climate variability is mostly associated with flooding in coastal areas and drought in both arid and semi-arid areas (especially Zamfara State). A flood is an overflow of a large amount of water beyond its normal limits, especially over  what is  normally dry land (Oxford English Dictionary, 2016), while drought is the consequence of a natural reduction in

the amount of precipitation received over an extended period of time – usually a season or more in length (Wilhite, 1993). The International Panel on Climate Change (IPCC, 2008) predicts that climate change over the next century will affect rainfall pat-terns, river flows and sea levels all over the world. For many parts of the arid regions there is an expected decrease in precipita-tion of 20% or more over the next century (Arab Water Council, 2009; Srinivasa Rao et al., 2016). Coastal areas are vulnerable to increasing sea levels, flooding, storm surges and stronger winds. Due to the rise in sea levels projected throughout the twenty-first century and beyond, coastal systems and low-lying areas will increasingly expe-rience adverse impacts such as submer-gence, coastal flooding and coastal erosion (European Commission, 2014; IPCC, 2014).

Weather and climate always have the potential to directly prevent children from

accessing the benefits of education, for example due to flooding of paths/roads which lead to schools, or the fact that drought and its associated economic con-sequences impede parents’ ability and will-ingness to allow their children to attend school. The floods of 2000 in Mozambique lowered the country’s Gross Domestic Product (GDP) by about 12%, and the 1992 drought reduced Zimbabwe and Zambia’s GDPs by about 9% (UNDP, 2004). The impact of floods on education in Zambia in terms of school attendance was attributed to damage to infrastructure such as bridges, culverts, classroom blocks and toilets. The most affected districts reported a 40–50% reduction in school attendance. School chil-dren are unable to cross streams/rivers that have flooded, and collapsed culverts and bridges rendered routes to schools inacces-sible (ZVAC, 2007). Flooding in the Mekong Delta of Vietnam claimed hundreds of lives,

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the vast majority being young children. In the year 2000, 400 children died; in 2001 the deaths of over 300 children were recorded; in 2002, children accounted for 99 of a total of 106 mortalities in the Delta (UNICEF, 2002). High temperatures may directly interfere with teachers’ ability to teach and children’s ability to learn (Amssalu, 2003).

Besides climate, a number of drivers – namely socioeconomic status (SES), the absence of professional role models, culture and parental beliefs – affect school attend-ance and dropout from school (Adejuwon, 2016). Bell et  al. (1994) observed that SES affects school attendance and that children of working parents with lower SES are fre-quently required to babysit siblings. Nicaise et al. (2000) and Natriello (2002) noted that the absence of professional role models in a community may hinder perception of the value of education. Children and youth who gain a deeper knowledge of environ-mental destruction and are empowered to take personal and social action to build sustainable futures will grow up to be adult citizens who are better prepared and moti-vated to join the global effort to save the Earth and preserve the future of humanity (Kagawa and Selby, 2010). Studies of culture by Admassie (2003), in rural Ethiopia, and Boyle et  al. (2002), in the poorest house-holds in Bangladesh, Nepal, Sri Lanka, Kenya, Uganda and Zambia, showed that many households have a preference for the education of boys over girls. They reiterated that in some cultures, girls are left to take on domestic responsibilities, and boys are often favoured with respect to education when parents have to choose who is to enrol in and attend school. Akresh (2008) points out that the decision to enrol and keep a child in school involves parental beliefs and expecta-tions about the value of schooling. However, climate still affects most of these drivers.

The relationship between climate and school attendance is a matter of cause and effect. There is a chain reaction, with the livelihoods of the parents having a direct effect on their children and notably affecting their school attendance. Drastic reductions in income result in difficulty in bearing the cost of edu-cation (school fees, school uniform, books and other necessary materials) of children. In many cases, the children engage in begging, fetching water, livestock pasturage, early mar-riage (especially girls) and so on (Apeldoorn, 1977), instead of attending school. The aim of this study is to fill a gap in the literature on climate variability and school attendance in Zamfara State; in particular, the dichotomy in male–female school attendance in the region is examined via the following processes:

· examination of the variability in school attendance of male and female pupils in the study area;

· examination of climate variation over time in the study area;

· identification of drought years in the study area;

· examination of the dropout of male and female pupils from primary schools in the study area;

· examination of the relationship between male and female school attendance in the study area; and

· assessment of the effect of climate variabil-ity on school attendance and dropout of male and female pupils in the study area.

Study areaThe study area, Zamfara State, is situated in the semi-arid part of Nigeria. It lies between latitude 10°N and 14°N and longitude 4°E and 8°E, covering an estimated land area of 38  418 km (Figure 1). Agriculture is the mainstay of the economy of Zamfara State, and over 80% of the population are farmers (Online Nigeria, 2003; Daily Trust, 31 October 2010). Major agricultural products include millet, guinea corn, maize, rice, groundnut, cotton, tobacco and beans (Online Nigeria, 2003).

The climate of Zamfara State is tropi-cal, and it is governed by the Intertropical Discontinuity (ITD; Adejuwon, 2016). The ITD separates the tropical maritime (mT) air mass of the Atlantic Ocean from the dry tropical continental (cT) air mass of the Sahara desert. The air-mass change is a

monsoon,1 moving (unsteadily) north from May and (unsteadily) south from September, bringing moist air inland across West Africa as far as the Sahel (Galvin, 2008). The ITD determines the penetration of the moist air masses (Adejuwon et  al., 1990). Rain falls when the mT air mass influences an area, while dryness prevails when an area is con-trolled by the cT air mass. The climate exhib-its marked wet and dry seasons: the mT air mass predominates during the wet season (June to September) in Zamfara, while the cT air mass predominates during the dry season (October to May; Mamman, 2000).

Annual rainfall varies from 676 to 1507mm (1970–2006), and the rainfall amount varies with direction and decreases from south to north. High relative humidity is experi-enced in the wet season, and there is lower humidity – of about 30% – in the dry sea-son (Oboli, 1967). During the Harmattan in January, when the cold, dry and dust-laden northeast trade winds blow from the Sahara Desert under cloudless conditions (Adejuwon, 2016), the mean relative humid-ity is close to 20%, while temperatures can be as low as 9°C throughout the day. At times, afternoon temperatures can rise to as high as 30°C, while the relative humidity falls to under 10%. Thick dust is prevalent during this period.

The seasonal temperature range is between 26 and 30°C (Mistry, 2000), while the mean annual temperature is 27°C. The extreme diurnal and seasonal range is affected by seasonal and latitudinal variations. The high-est temperatures are normally in the hot sea-son, from March to April, while the minimum

Figure 1. Map of Zamfara State showing the sampling locations.

1A monsoon is a seasonal shift in wind direction and pressure distribution that causes a change in precipitation.

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temperatures are usually recorded between November and February.

MethodologyData collectionRainfall and temperature (climate) data for Gusau station (the only synoptic station in the state) were collected from the archive

of the Nigerian Meteorological Agency and school enrolment and attendance data for 12 primary schools were obtained from four Zamfara State local government archives (Gusau, Kaura-Namoda, Anka and Talata-Mafara) for the period 1970 to 2006, using purposive and systematic sampling techniques. The advantages of these techniques are highlighted in Adejuwon (2016).

Data analysisThe descriptive statistics used include mean, frequency and percentages. School attend-ance data were subtracted from enrol-ment data to produce the dropout figures. Bivariate (Spearman’s) correlation was used to examine the relationship between climate and school attendance of male and female pupils, and the pairwise t-test was used to

Figure 2. School attendance of male and female pupils in Zamfara State, Nigeria.

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examine the difference in school attendance between male and female pupils. The annual rainfall and temperature variability were ana-lysed using the standardised rainfall anomaly index (SAI; Adejuwon, 2016). This technique determines the departure of the annual rain-fall and temperature values from normal.

Results and discussionTwenty-three out of the 37 years (1970–2006) in Zamfara State were character-ised by drought, while rainfall was above average for 14 years (1978/1979, 1988, 1991–1994, 1996, 1998/1999, 2003–2006; Adejuwon, 2016). Drought was mild in 19 out of the 23 drought years and was more pronounced in 1970, 1984, 1987 and 1990, when it ranged from moderate to severe. Male and female school attend-ance decreased and dropout increased in most schools during these periods. Male attendance varied from 30 pupils in 1970 at Yelwa Model Primary School (YMPS) in Talata-Mafara to 3430 in 2001 at Township 1 Special Model Primary School (T1SMPS) Gusau, while female attendance varied from 4 pupils in 1970 at JNIMPS, Gusau to 3380 in 2006 at T1SMPS Gusau. Male and female school attendance was generally lower at Wuya Model Primary School (WMPS), Anka, JNIMPS, Gusau and Mamuda Pilot Primary School (MPPS), Kaura Namoda than at other schools (Figure 2). Bashar Special Model Primary School (BSMPS), Kaura-Namoda is the only school where attendance for both males and females was greater than 500 pupils throughout the period of study. The difference in attendance figures for male and female pupils is small at BSMPS, Kaura-Namoda, where 53.17% of pupils were male and 46.83% were female, and widely differ-ent at the rest of the schools. In fact, female

attendance figures were less than 10% of those for males at Anka Nizzamiyya Primary School (ANPS) and Anka Model Primary School (AMPS), Anka. Male attendance was highest at T1SMPS, Gusau in 2001, while female attendance was highest at A Tunalim Primary School (ATPS), Talata-Mafara in 2006 (Table 1). School attendance of male pupils was higher than that of female pupils in all 12 schools, accounted for 71.52% of total school attendance in Zamfara State, and var-ied from 53.17% at BSMPS, Kaura-Namoda to 92.26% at AMPS, Gusau (Table 1).

School attendance is generally lower for girls than boys, for cultural rather than cli-matic reasons. Many households favour the education of boys over girls (Boyle et  al., 2002; Admassie, 2003). The reason for less schooling of girls than boys in the study area is that girls are given away in mar-riage very early in life, often at an age of less than 11 years, depending on puberty. Studies have discovered that child marriage leads to illiteracy, as many girls who marry as children are deprived of a basic educa-tion. In relation to the link between illiter-acy and child marriage in Nigeria, the 2008 National Demographic and Health Survey (NPC, 2008) revealed that there was a higher level of illiteracy among women in Northern Nigeria than any other part of the country (Braimah, 2014). Statistics of the National Demographic and Health Survey showed that 68% of women in the northeast and 74% of women in the northwest had no formal education, and the reason for this astonishing fact was the practice of child marriage in those regions (NPC, 2008). In the north, girls who have started menstru-ating are considered mature for marriage; the age at which menstruation begins varies between individuals, and a girl as young as 12-years-old can be given away for mar-

riage based on the fact that she has started menstruating (Elizabeth, 2009). Most often, these children are either not sent to school at all or are withdrawn early. Poverty has also been identified as one of the underly-ing reasons for child marriage. According to the National Bureau of Statistics, the rate of poverty is 77.7% in northwestern Nigeria (BBC, 2012; Premium Times, 2012). Otoo-Oyortey and Pobi (2003) asserted that, due to endemic poverty among the Hausa-Fulani in Northern Nigeria, female children are viewed as an additional burden on fam-ily resources. Hence, the betrothal of female children is used as a strategy for family sur-vival. Erulkar and Muthengi (2009) noted that child marriage is advantageous to poor families in rural locations, as betrothal of girls at a young age relieves parents of the costs and responsibilities of raising a girl. In many traditional settings globally, poor families use the early marriage of daughters as a tactic for reducing their own economic susceptibility, shifting the economic weight related to a daughter’s care to the husband’s family. Child marriage is also seen and used as a method for the preservation of the ‘vir-tue’ of girls. The underlying principle for this practice is to guarantee the preservation of virginity of women and family honour by ensuring that women do not become preg-nant out of wedlock. Based on these ideas, it is not exceptional to find children mar-ried at the age of 10 in Northern Nigeria. Girls are left to take on domestic respon-sibilities, while boys are given preference when parents must decide who attends school. Cultural beliefs in this region lead to girls being raised to be dependent and to do household work. They are sometimes traded at a price as brides (Pool, 2002).

Figure 3 shows the dropout of male and female pupils from schools in Zamfara State.

Table 1

Male and female school attendance figures for Zamfara State.

S/N School No. of male attendees

Male attendance as % of total attendance

No. of female attendees

Female attendance as % of total attendance

1 ATPS Talata-Mafara 29314 66.00 15375 34.00

2 DAMDMPS Talata-Mafara 23934 53.60 20715 46.40

3 YMPS Talata-Mafara 25411 63.34 14710 36.66

4 ANPS Anka 33566 90.93 3349 9.07

5 WMPS Anka 5093 64.46 2808 35.54

6 AMPS Anka 47285 92.26 3966 7.74

7 JNIMPS Gusau 9003 71.12 2982 28.88

8 T1SMPS Gusau 65231 80.81 15495 19.19

9 DMPS Gusau 18982 64.44 10473 35.56

10 BSMPS Kaura-Namoda 27002 53.17 23780 46.83

11 NMPS Kaura-Namoda 37788 73.90 13348 26.10

12 MPPS Kaura-Namoda 12795 66.04 6579 33.96

Total 335404 71.52 133580 28.48

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School dropout varied from 1 to 200 male pupil and 1 to 100 female pupils. Although 1979, 1988, 1996 and 2003–2005 were not drought years, there was nevertheless drop-out of pupils in some schools. This is because the effects of drought extend beyond the years of drought occurrence. The impacts of a drought increase slowly, often accumu-late over a considerable period, and may lin-ger for years after termination (Mishra and Singh, 2011). The dropout throughout the investigation period consisted of a total of

7569 male and 5306 female pupils (58.79% of dropout pupils were male, and 41.21% were female; Table 2). Male pupils who dropped out accounted for 1.62% of the total school attendance, while female pupils who dropped out accounted for 1.13%. Despite the fact that females made up 28.48% of the entire population of pupils, 41.21% of all dropouts were female. The dropout rate of female pupils is larger than that of their male counterparts in 7 out of the 12 schools. Since early marriage is encouraged among

females, many female pupils end up married rather than educated. Other contributory factors to the dropout of female pupils dur-ing drought in the study area include walk-ing long distances to collect water and the inability to use water for washing. Dropout becomes prevalent when the parents’ means of livelihood are affected by drought.

Drought problems result in a chain reac-tion – the livelihood of the parents having a direct effect on their children and notably affecting their school attendance. Drastic

Figure 3. Dropout of male and female pupils in Zamfara State, Nigeria.

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Table 2

Male and female school dropout figures for Zamfara State.

S/N SchoolMale pupil

dropoutMale dropout as

% of total dropout Female dropout

Female dropoutas % of total dropout

1 ATPS Talata-Mafara 275 46.22 320 53.78

2 DAMDMPS Talata-Mafara 1117 45.65 1330 54.35

3 YMPS Talata-Mafara 347 36.26 610 63.74

4 ANPS Anka 1786 81.70 400 18.30

5 WMPS Anka 411 56.07 322 43.93

6 AMPS Anka 1682 81.53 381 18.47

7 JNIMPS Gusau 291 60.12 193 39.88

8 T1SMPS Gusau 120 36.81 206 63.19

9 DMPS Gusau 589 66.11 302 33.89

10 BSMPS Kaura-Namoda 152 43.93 194 56.07

11 NMPS Kaura-Namoda 280 47.78 306 52.22

12 MPPS Kaura-Namoda 519 41.16 742 58.84

Total 7569 58.79 5306 41.21

Table 3

Bivariate correlation (r) between annual rainfall and school attendance of male and female pupils in Sokoto-Rima River Basin.

School Correlation coefficient (r)

Coefficient of determination (r2; %)

Male Female Male Female

ATPS Talata-Mafara 0.441b 0.468b 19.44 21.90

DAMDMPS Talata-Mafara 0.459b 0.462b 21.07 21.34

YMPS Talata-Mafara 0.457b 0.444b 20.88 19.71

ANPS Anka 0.207 0.255 4.28 5.06

WMPS Anka 0.144 0.118 2.07 1.39

AMPS Anka 0.258 −0.008 6.66 0.00

JNIMPS Gusau 0.483b 0.509b 23.33 25.91

T1SMPS Gusau 0.399b 0.494b 15.92 24.40

DMPS Gusau 0.480b 0.461b 23.04 21.25

BSMPS Kaura-Namoda 0.460b 0.463b 21.16 21.44

NMPS Kaura-Namoda 0.455b 0.425b 20.70 18.06

MPPS Kaura-Namoda 0.385a 0.253 14.82 6.40ar is significant at 0.05 level (aα ≤ 0.05). br is significant at 0.01 level (bα ≤ 0.01).

reductions in farmers’ incomes hinder their abilities to take care of their families, includ-ing their ability to meet their children’s edu-cational needs. When there is not enough to eat, school can quickly become an after-thought (UNICEF, 2012). This is the situa-tion in Zamfara State. UNICEF (2007) noted that children leave school at the time of drought because they cannot afford sup-plies and school fees, or because they have nothing to eat during the school day. Some of these children beg or steal, and some of them attend school irregularly. A child who is absent from school or attends irregu-larly will perform poorly and may be forced to repeat. Repetition lowers a pupil’s self

esteem and attitudes towards schooling, and this increases the likelihood of them dropping out of school (Chimombo, 2000). The total number of male dropout pupils was greater in the study area because male children were invariably asked to irrigate and tend to crops as a result of reductions in family income, and to look after livestock to prevent the family from losing these important animals during drought, while the adults find other means of making a living (Apeldoorn, 1977).

The school attendance record showed a steady increase (except in 1975) in both male and female attendance at Dr A.M. Dogo Model Primary School (DAMDMPS),

Talata-Mafara during the period of study. A possible reason is that most families might have engaged in other means of making a living to cushion the effects of drought. It has been reported that most people sell household goods or land, plant drought resistant crops, plant crops as usual, engage in trading activities, depend on other peo-ple for sustenance and engage in irriga-tion farming to augment losses during drought (Apeldoorn, 1977). According to Apeldoorn (1977), dependence on other people for sustenance includes accept-ing gifts of food from inside the villages or from relatives outside, men accept-ing their wives’ contributions to general household expenses, begging, and receiv-ing relief from government and voluntary organisations. Individuals, organisations, and Nigerian Government bodies were involved in the donation of relief materials in drought-affected areas during drought periods. During the period 1972–1974, relief donors included the Federal Government, the charity sector spearheaded by the Catholic Church, voluntary contribu-tions and the governments of unaffected states (Daily Times, 5 October 1973). The Federal Government began to contribute to drought relief in the affected states in 1972. A sum of 10 million naira in grants (later increased to 11 million naira) was allo-cated by the Federal Military Government to the governments of the affected states for immediate relief of the victims, with half of the money for a human relief pro-gramme (which included the purchase of grains to be sold at controlled prizes) and half for a livestock relief programme (which included the purchase of livestock feed and the expansion of water supplies; New Nigerian, 16 January 1973). The Federal Government also gave an interest-free loan

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Table 4

Bivariate correlation (r) between temperature and school attendance of male and female pupils in Sokoto-Rima River Basin.

School Correlation coefficient (r) Coefficient of determination (r2)

Male Female Male Female

ATPS Talata-Mafara 0.140 0.200 1.96 4.00

DAMDMPS Talata-Mafara 0.209 0.196 4.37 3.84

YMPS Talata-Mafara 0.208 0.200 4.32 4.00

ANPS Anka −0.128 0.235 −1.64 5.52

WMPS Anka 0.035 0.175 0.12 3.06

AMPS Anka −0.102 0.220 −1.04 4.84

JNIMPS Gusau 0.190 0.131 3.61 1.72

T1SMPS Gusau 0.159 0.206 2.53 4.24

DMPS Gusau 0.168 0.194 2.82 3.76

BSMPS Kaura-Namoda 0.196 0.189 4.37 3.57

NMPS Kaura-Namoda 0.198 0.243 3.92 5.90

MPPS Kaura-Namoda −0.090 0.173 0.81 2.99

Table 5

Pairwise t-test for male–female school attendance in Zamfara State.

School Paired differences t-value Degrees of freedom

Significance (2-tailed)Mean Std.

deviation95% confidence interval of the difference

Lower Upper

ATPS Talata-Mafara 376.73 362.65 255.82 497.64 6.32 36 0.000

DAMDMPS Talata-Mafara 87.00 43.06 72.64 101.36 12.29 36 0.000

YMPS Talata-Mafara 289.22 208.37 219.74 358.69 8.44 36 0.000

ANPS Anka 816.68 579.39 623.50 1009.85 8.57 36 0.000

WMPS Anka 61.76 53.55 43.90 79.61 7.02 36 0.000

AMPS Anka 1161.32 677.78 935.34 1387.31 10.42 36 0.000

JNIMPS Gusau 162.73 55.08 144.37 181.09 17.97 36 0.000

T1SMPS Gusau 1344.22 1062.57 989.94 1698.50 7.70 36 0.000

DMPS Gusau 229.97 174.81 171.69 288.26 8.00 36 0.000

BSMPS Kaura-Namoda 87.08 44.03 72.40 101.76 12.03 36 0.000

NMPS Kaura-Namoda 660.54 267.58 571.33 749.76 15.02 36 0.000

MPPS Kaura-Namoda 168.00 40.10 154.63 181.37 25.49 36 0.000

of 10 million naira to affected states for the improvement of grain production, 5 million naira for the purchase of livestock feed, and 20 million naira to buy grains for distribu-tion to victims of drought (New Nigerian, 1 October 1973, 11 November 1973, 21 November 1973; Daily Times, 5 October 1973, 21 December 1973).

The results of bivariate correlation analysis of the relationship between rain-fall and school attendance for male and female pupils in Zamfara State are shown in Table 3. Rainfall showed a significant positive (P ≤ 0.05) relationship with school attendance for male pupils in 9 schools and for female pupils in 8 schools. This indi-cates that males are more likely to attend school than females. The correlation coef-ficients for male pupils varied from r = 0.385 at MPPS Kaura-Namoda to r = 0.483

at JNIMPS Gusau, while the coefficient for female pupils varied from r = 0.425 at Namoda Model Primary School (NMPS) Kaura-Namoda to r = 0.509 at JNIMPS Gusau. This shows that an increase in annual rainfall over the period of consid-eration increases school attendance. The extent of these relationships ranged from 14.82 to 23.33% for male pupils and 18.06 to 25.91% for female pupils.2 This indicates that, apart from climate, there are other factors responsible for school attendance and dropout in the study area. Rainfall is not significantly related to male or female school attendance at P ≤ 0.05 for all three schools at Anka (ANPS Anka, AMPS Anka, WMPS Anka), or to female school attend-

ance at MPPS Kaura-Namoda. Additionally, temperature showed no significant correla-tion with school attendance of males or females at P ≤ 0.05 (Table 4). The pairwise t-test results varied from t(36) = 6.32, P > 0.05, CI0.95 255.81, 497.64 at ATPS Talata-Mafara to t(36) = 25.49, P > 0.05, CI0.95 154.63, 181.37 at MPPS Kaura-Namoda (Table 5). This indicates that there is a significant difference between male and female school attendance at all of the schools observed over the study period; thus we can conclude that, in addition to climate, there are other factors that affect school attendance and dropout of pupils from school in the study area. Socioeconomic status, absence of profes-sional role models, culture and parental belief have been identified as some of these factors in other studies, such as those

2The relationship between annual rainfall and school attendance.

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of Bell et  al. (1994), Nicaise et  al. (2000), Natriello (2002), Admassie (2003), Akresh (2008), and Kagawa and Selby (2010).

ConclusionThe results of this study show that males account for over two-thirds of the pupil pop-ulation and enrol and attend school at higher rates than female pupils at all schools; it was also found that the percentage dropout of female pupils is higher than that of their male counterparts in more than half of the schools. The variation in attendance of male pupils by school, and the total attendance and drop-out of male pupils from different schools is greater than that of female pupils. The results also show that less than 3% (1.62% male and 1.13% female) of the total attendance dropped out of school; about 60% of dropout pupils were male and 40% were female, and about 2% of the total male pupil population and 4% of the total female population dropped out of school. Temperature showed no sig-nificant relationship with school attendance for male or female pupils. Rainfall had a more significant relationship with male attendance than female. The extent to which rainfall sig-nificantly determined school attendance var-ied from 14.82 to 25.91%. A pairwise t-test showed a significant difference between male and female school attendance. This study concludes that (1) climate variability affects male pupils more than female pupils and (2) attendance is generally lower for girls than boys, for cultural rather than climatic reasons.

The consequence of cultural values that negatively influence female education is less schooling. A change in attitude and legislation against child marriage are the solutions. It is also clear that reduced rain-fall results in decreased attendance at (and increased dropout from) schools.

Correspondence to: Joseph Adejuwon

adejoseph2003@yahoo.com

© 2018 Royal Meteorological Society

doi:10.1002/wea.3021

ReferencesAdejuwon JO. 2016. Effect of climate vari-ability on school attendance: a case study of Zamfara State in the semi-arid zone of Nigeria. Weather 71: 248–253. Adejuwon JO, Balogun EE, Adejuwon SA. 1990. On the annual and seasonal pat-terns of rainfall fluctuations in sub-saharan West Africa. Int. J. Climatol. 10: 839–848.Admassie A. 2003. Child labour and schooling in the context of a subsistence rural economy: can they be compatible? Int. J. Edu. Dev. 23(2): 167–185.Akresh R. 2008. School enrolment impacts of non-traditional house-hold structure. University of Illinois at Urbana-Champaign. https://netfiles.uiuc.edu/akresh/www/Research/AkreshSchoolEnrolment (accessed 6 May 2016).Amssalu T. 2003. Socio-economic fac-tors affecting female child labour and school attendance: the case of Menge and

Komosha Woreda of Benishangul Gumuz National Regional state. PhD Thesis. Addis Ababa University: Addis Ababa.Apeldoorn JV. 1977. Drought in Nigeria. Draft Report, Vol. 2, Lessons of the 1972–1974 Disaster. Center for Social and Economic Research, Ahmadu Bello University: Zaria, Nigeria.Arab Water Council. 2009. Vulnerability of arid and semi-arid regions to climate change – Impacts and adaptive strategies. IUCN perspectives on water and climate change adaptation: Cairo, Egypt.BBC. 2012. Nigerians living in poverty rise to nearly 61%. BBC News. http://www.bbc.com/news/world-africa-17015873 Bell AJ, Rosen LA, Dynlacht D. 1994. Truancy intervention. J. Res. Dev. Educ. 27: 203–211.Boyle S, Brock A, Mace J et al. 2002. Reaching the Poor: The ‘Costs’ of Sending Children to School. A Six Country Comparative Study Synthesis Report. DFID: London.Braimah TS. 2014. Child marriage in Northern Nigeria: Section 61 of Part I of the 1999 Constitution and the protection of children against child marriage. African Human Rights Law J. 14: 474–488.Chimombo J. 2000. Classroom, School and Home Factors that Negatively Affect Girls Education in Malawi. Centre for Educational Research and Training: Zomba, Malawi. Elizabeth E. 2009. Child marriage: an undying culture? The Tide http://www.thetidenewsonline.com/2009/12/28/child-marriage-an-undying-culture (accessed 30 June 2016).Erulkar AS, Muthengi E. 2009. Evaluation of Berhane Hewan: a program to delay child marriage in rural Ethiopia. Int. Perspect. Sex. Reprod. Health 35(1): 6–14. European Commission. 2014. IPCC report on climate impacts: “It’s time to get seri-ous”. Climate Action. ec.europa.eu/clima/news/articles/news_2014033101_en.htm (accessed 30 June 2016).Galvin JFP. 2008. The weather and climate of the tropics: part 6 – Monsoons. Weather 63: 129–137.International Panel on Climate Change (IPCC). 2008. Climate change and water, in Intergovernmental Panel on Climate Change, Technical Report IV. Bates BC, Kundzewicz ZW, Wu S et al. (eds). IPCC Secretariat: Geneva, Switzerland, 210 pp.IPCC. 2014: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Summaries, Frequently Asked Questions, and Cross-Chapter Boxes. A Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Field CB, Barros VR, Dokken DJ et al. (eds). World Meteorological Organization: Geneva, Switzerland, 190 pp.Kagawa F, Selby D. 2010. Education and Climate Change: Learning in Interesting Times. Routledge: New York, NY.Mamman AB. 2000. Sokoto State, in Nigeria: A People United, A Future Assured: Survey of States, Millennium Edition, Volume 2. Mamman AB, Oyebanji JO, Petters SW (eds). Federal Ministry of Information : Abuja, Nigeria, pp 499–514. Mishra AK, Singh VP. 2011. Drought modeling – A review. J. Hydrol. 403(1–2): 157–175.

Mistry J. 2000. World Savanna-Ecology and Human Use. Pearson Education: Harlow, UK, pp 20–25; 108–131.National Population Commission (NPC). 2008. Nigeria Demographic and Health Survey 2008: Federal Republic of Nigeria, Abuja, Nigeria and ICF Macro, Calverton, Maryland, USA.Natriello G. 2002. Dropouts, school leav-ers and truancy, in The Encyclopedia of International Education. Guthrie J (ed.). Volume 3. BPC Wheatons: Oxford, UK, pp 1602–1607.Nicaise I, Tonguathai P, Fripont I. 2000. School Dropout in Thailand: Causes and Remedies. Katholieke Universiteit Leuven: Flanders, Belgium.Oboli, HON. 1967. An Outline of West Africa. Harrap and Co.: London, pp 115–126. Online Nigeria. 2003. Natural resources and potentials for development. http://www.onlinenigeria.com/zamfara-state/?blurb=397 (accessed 30 June 2016).Otoo-Oyortey N, Pobi S. 2003. Early mar-riage and poverty: exploring links and key policy issues. Gender Dev. 11(2): 42–51.Oxford English Dictionary. 2016. Flood. Oxford University Press: Oxford, UK.Pool G. 2002. Child marriage. Foundation for Women’s Health, Research and Development. http://forwarduk.org.uk/key-issues/child-marriage/ (accessed 16 April 2016).Premium Times. 2012. 112 million Nigerians living below poverty level – report. http://www.premiumtimesng.com/news/4211-112million_nigerians_liv-ing_below_poverty_level.html (accessed 24 April 2016).

Srinivasa Rao NK, Shivashankara KS, Laxman RH. 2016. Abiotic Stress Physiology of Horticultural Crops. Springer (India): New Delhi.UNDP (United Nations Development Program). 2004. Reducing Disaster: A Challenge for Development: Global Report. United Nations Development Program: New York, NY.UNICEF (United Nations Children’s Fund). 2002. Psychosocial impact of child drowning deaths in the Mekong River Province of Dong Thap: a preliminary assessment. United Nations Children’s Fund: Hanoi, Vietnam.UNICEF. 2007. Children and Climate Change. United Nations Children Fund: New York, NY.UNICEF. 2012. Food shortages force chil-dren to drop out of School in Niger. http://www.unicef.org/health/niger_61582.html (accessed 25 July 2016).Wilhite DA. 1993. The enigma of drought. In DA Wilhite (ed). Drought Assessment, Management, and Planning: Theory and Case Studies. Kluwer Academic: MA, USA. pp 3–15.ZVAC (Zambia Vulnerability Assessment Committee). 2007. Rapid Flood Impact Assessment Report. ZVAC: Lusaka.