African Population Studies Union for African Population Studies ISSN: 0850-5780 Vol. 22, Num. 1, 2007, pp. 87-106

African Population Studies/Etude de la Population Africaine, Vol. 22, No. 1, 2007, pp. 87-106

Henry V. Doctor

University of the Western Cape, Department of Statistics, Private Bag x17, Belville 7535, South Africa, Email: hdoctor@uwc.ac.za , Tel: +27 76 104 4001,  Fax: +27 21 959 2909

 Code Number: ep07005

Abstract

Has the Navrongo Community Health and Family Planning (CHFP) Project been successful in changing fertility preferences? Using linked data from panel surveys conducted in the Kassena-Nankana district of northern Ghana in 1995 and 2002 as part of the CHFP, we compare reproductive behavior against prior fertility preferences and show the transition of women from wanting to not wanting more children. Descriptive and multinomial logistic regression results show that the acceptance of smaller family sizes (i.e., 1–3 children) and high proportions of women reporting no intention to have more children in the future reflect that the combination of mobilizing community volunteerism and retraining and redeploying nurses to village-based locations results in a change in reproductive behavior. Implications for policy are discussed.

Keywords: Family planning;Fertility; Ghana; Longitudinal data

Introduction

Results from the 2003 Ghana Demographic and Health Survey (GDHS) show that fertility in Ghana has declined from 6.4 births per woman in 1988 to 4.4 births per woman during the last five years, a 2-child drop in fertility over the last 15 years. This decline has been observed in every age group with fertility levels among women under age 35 declining by about 25% between 1988 and 1998 surveys (GSS, NMIMR and ORC Macro, 2004; GSS and MI 1999). However, differences in fertility levels by place of residence are pronounced with rural women having 2.5 more children than their urban counterparts. Fertility is highest in the Northern Region with 7 births per woman and lowest in the Greater Accra Region with 2.9 births per woman.

There are several factors accounting for the observed fertility decline in Ghana. The 2003 GDHS reports a 5% decrease in the percent of women currently in union over the last five years from the survey—from 65% in 1998  to 62% in 2003. This decline has been most common in the youngest (15−29) and oldest (44−49) age groups. There is also a trend towards late entry into marriage and a decline in the proportion of women getting married by age 15 from 11% among women aged 40−44 to 3% among those currently aged 15−19 at the time of the survey. These changes are also consistent with results from other surveys that show a decline in recent (i.e., prior to the survey) sexual activity in Ghana compared with other African countries. For example, results from the 1998 GDHS show that about 40% of women (15−49) were sexually active in the four weeks prior to the survey compared with, for example, 57% of women in Niger, 58% in Cameroon, and 63% in Senegal (GSS and MI 1999). According to the 2003 GHDS, the proportion of women who were sexually active four weeks prior to the survey has stabilized at 1998 levels.¹ Other factors include an increase in age at first birth, longer birth intervals—with half of all births occurring more than three years after a previous birth, and a narrowing of the gap between desired and achieved family size as evidenced by the mean ideal number of children which declined from 5.5 in 1988 to 4.8 in 2003 (GSS, NMIMR and ORC Macro, 2004). Total fertility rate declined from 6.4 in 1988, to 5.2 in 1993, and stabilized at 4.4 in 1998 and 2003.

Knowledge of family planning is almost universal in Ghana, with 98% of currently married women having heard of at least one modern method of contraception. Contraceptive prevalence rate was also estimated at 25% in 2003. However, there are clearly other proximate determinants of fertility operating in Ghana that are beyond the scope of this paper.

The Ghanaian government and family planning officials are committed to the welfare of the people by ensuring that fertility levels remain at reasonable levels in all parts of Ghana. Despite the decline of fertility in Ghana, particularly in the urban areas, fertility levels in rural Ghana are still high. Current strategies to reduce fertility in rural Ghana focus on making contraception available to individual women in their communities. This strategy is based on findings from survey data that have indicated that many women have more children than they desire and that contraception would be used if methods were readily available in their rural and impoverished communities (Adongo et al, 1997). Thus, it is assumed that inaccessibility of modern contraception to women is one of the barriers to use and subsequent high levels of fertility. This paper examines whether the availability of family planning and community health services programs can alter fertility preferences of rural women in Ghana. Research on the role of community health and its influence on demographic outcomes in rural Ghana is important and useful in providing benchmarks for program planning and development.

The reproductive practices among the Kassena-Nankana of northern Ghana reduce fertility through prolonged lactational amenorrhea and prolonged postpartum spousal separation (Adongo et al, 1997: 1789). However, the calculus of conscious control can be improved by the Community Health and Family Planning (CHFP) project. One way to address this is to assess whether conscious control can be or has improved by the CHFP in the Kassena-Nankana district of northern Ghana.

Worldwide, it is acknowledged that the key factors that have been identified to influence fertility-limiting behavior as well as fertility preferences in developing countries include increased participation in formal schooling, urbanization, and the diffusion of Western ideas, among others. Most of these factors are associated with socio and economic development (Feyisetan and Casterline 2000). Specifically, social interactions have been identified as having a potential significance not only in the design of family planning programs in high-fertility settings (such as the CHFP) but also in influencing individual reproductive behavior (Casterline 2001; Feyisetan et al, 2003). Further, the effects of social learning and social influence are expected to exert an environment whereby individuals will be faced with the need to make fertility decisions in a changing environment (Montgomery and Casterline 1996). The introduction of the CHFP in northern Ghana has been a milestone in creating an environment whereby social learning and social influence becomes inevitable with implications on reproductive behavior.

What do preferences mean in contemporary rural Ghana? Has the CHFP altered women’s fertility preferences? Longitudinal surveys permit an assessment of the degree to which expressed intentions are consistent with subsequent behavior (Freedman et al, 1975). This article uses panel data containing linked records across two surveys conducted in Kassena-Nankana district of northern Ghana in 1995 and 2002² to compare reproductive behaviors against prior fertility preferences and to show when and where women change from wanting to not wanting more children. Specifically, we want to establish if there is variation in the fertility preferences of women in the four experimental cells of the CHFP. These surveys were conducted for the CHFP project “Navrongo Panel Surveys” in rural Ghana. The present study constitutes part of a more general investigation of the fertility impact of the CHFP in Kassena-Nankana district.

Study Design and Data

The Navrongo Health Research Centre (NHRC) is an institution of the Ghana Ministry of Health (MOH) that has been mandated (by the MOH) to research preventable causes of morbidity and mortality and related problems of high fertility in northern Ghana. The NHRC is located in the Kassena-Nankana district on the border with Burkina Faso. The social, ecological, and economic attributes of the study area are more representative of the Sahel population to the north of Ghana than of cultures and attributes of the coastal West African cultures in the south of Ghana (Adongo et al, 1997). Navrongo town is one of the towns in the district with access to communication facilities, tarmac roads, and electricity. Other towns include Paga and Chiana. Briefly, the Kassena-Nankana district is largely inhabited by rural, agrarian, and poor people. Poverty is widespread and stimulates out-migration. The largely wobbly agricultural production and increase in the population have compelled young adults to migrate to cities for temporary employment.

To address the need for practical field trials of community health services, the Government of Ghana launched the Navrongo CHFP in 1993 in order to test the demographic impact of different schemes for services being offered (Bawah 2002). Details of the CHFP have been extensively published elsewhere (see for example, Binka et al, 1995; Adongo et al, 1997; Pence et al, 2001; Bawah 2002; Feyisetan et al, 2003; Nyonator et al, 2003). In brief, the CHFP serves a broader, and international, need for a rigorous, controlled evaluation of organizational strategies for primary health service delivery in rural Ghana. The CHFP is a two armed community-randomized quasi-experiment that combines a program of community health and family planning services with an arm for mobilizing traditional leadership, communication and volunteerism. Four cells are implied because the arms are implemented independently, jointly, or not at all in four sub-district health centres (catchment areas) in three of the cells, with the fourth cell serving as a control and offers the usual government services at MOH service points. The three interventions were designed through consultations with MOH officials and village elders and groups. The zurugelu³ cell seeks to increase community involvement in health decisions by involving local people and volunteers in health planning and delivery of health activities and services.

The zurugelu approach consists of local volunteers (aka Yezura Zenna or YZ in the local language) who make compound visits rendering health services to community members. The YZs gave treatment to anyone with minor ailments such as malaria, headache, abdominal pains, etc., and referred patients to the community health officers (CHOs) where necessary. In the absence of health problems in a compound, YZ provided specific health educational talks concomitant with the situation of the compound. The YZs also traced immunization defaulters and advised them to report for immunization on the next outreach clinic days. In addition to rendering family planning services (especially condom distribution), YZs also distributed insecticide treated mosquito nets under the supervision of the CHO during monthly outreach clinics. During compound visits, the YZ sometimes carried along chemical for re-impregnating old mosquito nets.  In general, the YZ and CHO worked hand in hand and consulted each other on certain aspects of their work where necessary (Awogbo et al., 2004). 

The MOH mobilization cell tests the effectiveness of improving access to health services by retraining and redeploying CHOs from fixed clinics to village residences and assigning them doorstep service delivery responsibilities. The combined cell (i.e., CHO + YZ) uses both approaches and establishes close collaboration between the CHOs and the community leaders and volunteers. A comparison cell receives services according to standard MOH guidelines (Pence et al, 2001).

In order to reduce the effects of diffusion in the different arms of the intervention, treatments were delineated by entire paramount-chieftaincy areas, so that involvement of traditional leaders in the intervention areas would not contaminate the activities in neighboring treatment zones (Debpuur et al, 2002). Cells may be contaminated by differential access to primary-health-care facilities in sub-districts and in Navrongo town. Residents of Navrongo town are excluded from the analysis because Navrongo town, which borders the combined cell, is a relatively developed area with a possibility of influencing the inhabitants’ reproductive motives. Navrongo town is also developed as a market for agricultural goods and experiencing enhanced radio use and other communications that have opened the locality to new ideas and activities. These economic changes may lead to contamination effects thereby rendering exclusion of Navrongo residents from the analysis inevitable.

The CHFP has been longitudinally monitoring demographic dynamics in a population of about 143,000 since July 1993, with interventions beginning in 1995. The Navrongo panel surveys consist of a longitudinal follow-up of a random sample of women of reproductive age and their husbands. The initial sample for the panel survey was drawn from the Navrongo Demographic Surveillance System in 1993. Prior to 1993, a census of Kassena-Nankana district was conducted and each resident was assigned a unique identification number. A re-canvass of the population was done in July 1993 and since then the population has been monitored every 90 days in order to record demographic events taking place such as in- and out-migration, births, deaths, marriages, and other events (Binka et al, 1995). The 1993 survey instrument was modeled after the 1993 GDHS. The core questionnaire gathered information on respondent’s background, contraceptive use, reproductive histories, pregnancy, breastfeeding, and fertility preferences. The survey targets women and their husbands.

Because some of the questions in the 1995 panel survey⁴ are repeated annually, the impact of fertility preferences as reported in the baseline survey can be compared with preferences or reproductive behavior in 2002. Although the panel surveys are conducted annually, we examine the 1995 and 2002 panels in order to assess the changes in fertility preferences for a cohort of women over a reasonable long period of time. This is important because we observe intentions of a cohort of women in 1995 and follow them in 2002. The sample is restricted to women aged 15−42 in 1995 who move into the age group 22−49 in 2002.⁵ Observing women in annual surveys, for the purposes of this study, has got the disadvantage of censoring. We want to follow women for a period we think is substantial to influence their reproductive behavior.⁶ The baseline survey yielded a sample of 5,288 women aged 15−49 and 6,312 women were surveyed in 2002. The 2002 sample is roughly 19% greater than the 1995 sample because urban Navrongo which was not part of the 1995 sample was included beginning from the 1996 round. However, our sample for the present study is restricted to 3,676 currently married and ever-married women of reproductive age (i.e., 15−42) from the 1995 survey of whom we are most confident that linkages for 1,402 women in 2002 have been done correctly—about 38% of the original sample.⁷

Results

Basic characteristics of respondents are presented in Table A1 which compares characteristics of all women interviewed in the 1995 panel survey with those who were interviewed in both the 1995 and 2002. Except for minor differences in age and parity, respondents are comparable for all variables.⁸ Table A1 shows that respondents were younger than those interviewed in 1995 suggesting some form of out-migration, a common behavior among the Kassena-Nankana. About three out of every four women in both years were married, more than two-thirds of women were illiterate, and fertility is high with more women in the high-parity category. In addition, when asked about their future fertility intentions, at least 70% of women said that they want more kids.

Table A1. Percentage Distribution of All Women Interviewed in 1995 and Those Interviewed in Both 1995 and 2002, by Selected Characteristics, Navrongo Project Panel Surveys, Kassena-Nankana District, Northern Ghana

Note: ^*Excludes infecund women.

Measurement of Fertility Preferences

Both the baseline survey and the follow-up survey included the question: “Now I have some questions about the future. Would you like to have (a/another) child or would you prefer not to have (any/more) children?” This question was asked to non-pregnant women at the time of the survey. Possible answers were “have a/another child”, “no more/none”, and “infecund”, and “undecided/don’t know.” Analysis focuses on the first two and last response categories which are denoted as “yes”, “no”, and “undecided.” Table 1 shows the distribution of respondent’s desire about wanting any more kids by experimental cell and survey (Baseline or Follow-up survey). In the baseline survey, and among the women in the YZ catchment area, 32% of women whose actual number of children was greater than the ideal number of children wanted more kids whereas in the follow-up survey the percentages are significantly lower at roughly 28%. In general, the percentages in all the categories declined between the baseline and follow-up survey. The percentage of women who indicated that they did not want any more children also increased between the surveys. For example, women whose actual number of children was greater than the ideal number increased from roughly 5% to 7%. The undecided category did not change a great deal during the period. These results may be influenced by the confounding effect of age whereby younger cohorts may practice more fertility limiting behavior than their counterparts.

Table 1: Percentage Distribution of Desire About Wanting Any More Children in the Future, Kassena-Nankana District, Northern Ghana

Notes: “Actual” is the number of the women’s surviving children whereas “ideal” is the desired number of family size. Distribution excludes infecund women and the “not applicable” category. ^aTotal does not sum to 100.0 because of rounding.

In the CHO area, the trend is similar to the YZ area except that the magnitude of the decrease in percent is greater in the CHO area than the YZ area. For example, about 58% of women wanted more children despite their actual number exceeding the ideal number in the baseline survey whereas in the follow-up survey this percentage declined by about 18 points. Similar trends are also observed for the “no” and “undecided” categories. Therefore, comparing column one (“yes”) versus the YZ and the CHO areas, one sees that the decline in percentage is huge for the CHO area.

We then turn to the combined area which shows a difference of about seven points for the first (actual ≥ ideal) category between the two surveys. The percentage change in the comparison cell (regular) is very small compared to the three cells. This suggests that the CHO only approach has a greater impact on fertility preferences between the surveys compared with the other approaches. This part of the analysis provides evidence that retraining and redeploying trained nurses to village residences where they are easily accessible to the community can dramatically affect fertility preferences related to desire for wanting more kids based on the number of children which the woman already has.

Women with At Least One Child in the Baseline Survey

About half of the women in the baseline survey were aged between 15 and 31 years and they are thus highly likely to have another pregnancy, regardless of the desires they hold toward their current number of children. In Table 2, therefore, we restrict our analysis to those women in the baseline survey who had had at least one child at the time of the interview. This excludes women who were pregnant at the time of the baseline survey. We also exclude women who in 1995 were just about entering the menopausal period. The response variable is now whether the respondent began a pregnancy by the follow-up survey. We acknowledge that this approach may introduce bias in the estimates considering that some women might have started their pregnancy anytime between the baseline and the follow-up survey. In addition, women who were much older in 1995 may not have started another pregnancy after seven years from the previous survey. Nevertheless, assuming constant rates of starting another pregnancy between the baseline and follow-up survey, this exercise is representative of the reproductive behavior of these women.

Table 2: Percentage of Parity ≥ 1 Women Starting Another Pregnancy y 2002, by their Desire About Wanting Any More Children in 1995 and Experimental Cell, Northern Ghana

Note: The numbers in parentheses are the cell sizes. Excludes women who in 1995  were just about entering menopausal period.

In the YZ area, for example, there were nine women who started another pregnancy by 2002 out of those who said they wanted more children in 1995. Only one woman thought that she did not want any more children in 1995 but had started another pregnancy by 2002. In the CHO area, 20% of women wanting more children in 1995 started another pregnancy by 2002 and this is less by about 16 points compared with women from the combined cell. About 31% of women from the comparison area started a pregnancy by the follow-up survey. The desire of women to want more children seems to be consistent with the experimental effect. We observe that few women from the YZ area and the CHO area really started another pregnancy by the follow-up survey.

In the third column of Table 2, the percent of women who said they did not want more children in the baseline survey but started another pregnancy by the follow-up survey is lowest in the YZ area at roughly 6% followed by the CHO area at 17% with high percentages observed in the combined cell and comparison cell at roughly 47% and 29% respectively. Although the cell frequencies of women in the “undecided” category are very small, we see that two-thirds of the women in the comparison cell had started another pregnancy. Table 2 in general shows that reproductive behavior in Kassena-Nankana responds to the implementation of the CHFP.  

Shifts toward Acceptance of Small Family Sizes

In contemporary societies, lower fertility is the desired goal of most people and one way in the present study to measure the impact of the CHFP is to assess shifts in the acceptance of small family sizes between the two surveys. Table 3 presents this information in which women with living children were asked the following question: “If you could go back to the time when you did not have any children and could choose exactly the number of children to have in your whole life, how many would that be? Women with no living children were asked: “If you could choose exactly the number of children to have in your whole life how many would that be?” In both surveys, very few women (less than 3% in 1995 and less than 1% in 2002) were childless. These childless women have been excluded from the analysis. The results in Table 3 show that between 1995 and 2002 there has been an increase in the number of women accepting small (1−3) family sizes. For example, in the YZ area 9% of women in 1995 wanted small family sizes whereas in 2002 this percentage more than doubled at 20%. Similar increases are observed for the CHO (from 10% to 15%), the combined cell (from 9% to 15%), and the comparison cell (from 3% to 12%).

Table 3. Percentage Distribution of the Comparison Between Women’s Reports of Desired Family Size, by Experimental Cell and Survey Year, Northern Ghana

Notes: Excludes “Up to God” (no cases in 1995; 0.1% in 2002) and “Other responses”
 (32.8% in 1995 and 35.2% in 2002). Cell differences in 1995 are significant
(p=0.000) and not significant in 2002 (p=0.149).

Corresponding to the increase in the percent of women wanting small family sizes, we see that there has been a decline in the percent of women wanting big family sizes particularly the middle group (4−6). In the YZ area, the percentage of women wanting big family sizes declined by three points from 64% to 61% whereas the CHO decreased from 69% to 65%. The combined cell decreased from 67% to 62%. However, the controlled cell registered an increase from about 54% to 61% between the surveys. Looking at this trend, one sees a decline in the number of women wanting big family sizes but still the majority of women are concentrated in the 4−6 category and a substantial number of women still wanting 7 or more children. This is a sign that despite the efforts of the CHFP in promoting family planning and general health of individuals, fertility is still high.

Multivariate Analysis of Intention to Have Children in the Future

We employ multinomial logistic regression to analyze the effect of selected baseline covariates on women’s intention to have children in the future. Multinomial logistic regression is employed because intention to have children in the future is coded as a trichotomous variable (i.e., intends to have children; no intention; and undecided). The comparison category is intention to have children in the future. Table 4 presents regression results from modeling the dependent variable using the CHFP cell, family size (actual versus desired), respondent’s schooling, age group, type of marital union (polygamous or not), and religion. Ethnicity and husband’s schooling were not significant at the bivariate level and in multivariate models. Inclusion of these variables did not improve the models.

Table 4. Multinomial Logistic Regression Results (Odds Ratios) of Selected Baseline Covariates on Intention to  Have Children in the Future, Women (1995–2002)

Notes: *Significant at p<0.05; **p<0.01; ***p<0.001; ^†Islam and “Other” religion dropped due to few number of cases.
Estimates were not obtained for this category of religion; Ethnicity and husband schooling not significant in bivariate models and lead to poor model fit when included in the analysis

The odds ratios (OR) for Model 1 shows that women in the combined cell are almost twice (OR=1.95) as likely to report no intention of having children as those in the YZ cell. Similarly (same Model 1), the odds of being undecided about having more children in the future are higher (OR=2.47) among women in the combined cell than those in the YZ cell. After controlling for family size and respondent’s schooling in Model 2, the results are almost similar in magnitude and direction as those reported in Model 1. Controlling for age, type of marital union, and religion in the final model shows that being in the combined cell is associated with higher odds (OR=1.91) of reporting no intention of having children in the future than for women in the YZ cell. Significance is also observed for women in the CHO cell who are about 61% less likely to express no intention of having more children in the future than their counterparts in the YZ cell. Women aged 25–34 are about 17 times more likely to report no intention than women aged 24 and younger whereas those aged 35 and over have the highest odds (OR=72.91) of expressing no intention than the youngest women. The results further show that Christian women are 1.70 times more likely to report no intention of having children in the future than women practicing traditional religion. We find no significant effect between the CHFP experimental cell and reports of being undecided about having children among women. The only significant relationship among undecided women is observed in the middle age group (i.e., 25–34) and among older women with odds that are 9.21 and 30.41 respectively.  Women in polygamous unions are less likely (OR=0.50) to be undecided about having children in the future than those in monogamous unions. To a large extent, the regression results demonstrate the evidence that the combined cell has an impact on women’s reproductive preferences among the Kassena-Nankana.

Conclusion

When the women in the panel surveys were asked to indicate their desires about wanting any more children, they responded by stating their preferences for smaller families. Their responses are consistent with the expected change in the reproductive preferences due to the presence of volunteers and CHOs providing health service delivery in the communities. Fertility behavior between the surveys was largely a function of the Navrongo CHFP project. In the communities where there is intervention, women seem to show that their fertility preferences are in line with the objectives of the CHFP project. That is, women are generally shifting towards small family sizes although the fertility levels are still high.

These results must be placed in the context of the literature reviewed earlier. The decline in fertility is still comparatively modest. Levels of education are slowly increasing, economic activities are still challenging, and the demands of the traditional system in which the needs of the extended family outweigh the significance of individual behavior are still daunting.

The Navrongo panel data analyzed here derive from an experimental study of the liberalization of choice regarding family planning and health. These results are at least suggestive of where the Ghanaian government may want to scale up its community health service delivery and what approaches it should take. This is a generalization based on ideal types of fertility preference. There is no statistical warrant for generalizing our four experimental cells to all rural areas in northern Ghana, much less to all of Ghana. To some extent, our study is in accord with the generalization that door-to-door service delivery in Kassena-Nankana district indicates that more women have received the message of good health and family planning. Further, these results are consistent with the documented decline of fertility in the Upper East region of Ghana (Debpuur et al, 2002; GSS, NMIMR and ORC Macro, 2004).

Acknowledgements

Research reported in this paper was conducted while the author was a Mellon Research Fellow at the NHRC. The author would like to thank the Mellon Foundation through the Population Council for financial support and the NHRC for providing data for this research. Ayaga A. Bawah and James F. Phillips are acknowledged for their invaluable input on an initial version of this paper.

Notes

1. Although more recent estimates of the proportion of sexually active women from the countries referred to here (i.e., Cameroon, Niger and Senegal) are not readily available at the time of compiling this study, it is reasonable to expect that the magnitude of the difference with estimates from Ghana should not be very different.
2. There have been annual surveys between 1995 and 2002 but we focus on these two years in order to assess fertility preferences for a cohort of women who age over time and assess whether in a 7-year interval, their preferences are consistent with prior fertility desires.
3. In the local dialect, the translation for “zurugelu” is Alag gube ndekewgo, which means “cooperating together is strength” or “community togetherness.” This term is roughly equivalent to the Swahili word referring to the harambee spirit, used in Kenya to describe community activities requiring solidarity and volunteerism (Binka et al, 1995).
4. Hereafter the 1995 panel survey will be used interchangeably with “the baseline survey”.
5. This assumes that age reporting in the sample is perfect.
6. For example, we consider women who were aged 15 in 1995 and are now aged 22 in 2002. Their fertility behavior may be very sensitive to social changes such as the experiment compared with women who were aged 42 in 1995 and are now aged 49 in 2002.
7. We believe that this is a right linkage which is consistent with Bawah’s (2002) study linking women from the 1995 survey to those interviewed in 1997 where he was able to link about 65% of the original sample. The age restriction ensures that all cohorts represented in the baseline survey were also represented in the follow-up survey. We focus on ever-married women because they have been exposed to the risk of childbearing and thus are able to exercise or contemplate on various reproductive preferences either directly or indirectly.
8. This comparability has also been established by Bawah (2002) in his analysis of the effect of spousal communication on contraceptive use. He found that the characteristics of women who were interviewed in 1995 and those who were interviewed in both the 1995 and 1997 were highly comparable.

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