6 Perspectives

Want to improve malnutrition? Start with women’s rights, educating girls and hygiene

Nearly ten years ago, a paper in the journal The Lancet changed the way countries around the world approached improving nutrition.

The paper identified ten critical nutrition interventions – all of them direct nutrition interventions like micronutrient fortification, breastfeeding, and vitamin A supplementation. And it posited that if those interventions were scaled to reach 90 percent of children in the 34 countries where good childhood nutrition is most lacking, they would reduce stunting rates by 20 percent. These ten interventions became the standard roadmap to improving nutrition for health officials globally.

Over the last three years, my colleagues at SickKids, research partners around the world, and I have engaged in robust mixed methods research to determine how Ethiopia, the Kyrgyz Republic, Nepal, Peru, and Senegal achieved remarkable reductions in childhood stunting over the last 25 years. We expected to find that those same ten interventions identified in The Lancet would have been responsible for most of the improvement in stunting across each of these countries.

What we found was surprising.

Yes, direct nutrition interventions are critical and our research validates many of the findings of the Lancet article. But our evidence also highlights what the Lancet article didn’t capture – an equally powerful role for indirect nutrition interventions that are delivered outside of the health sector.

We estimate that these indirect strategies, such as interventions to improve women’s empowerment, girls’ education, poverty reduction and WASH, account for, on average, half of the stunting reduction those countries achieved. By country, these supportive nutrition strategies contributed anywhere from 33 percent of the stunting reduction in Peru to 63 percent in Ethiopia.

These findings, made as part of the new Exemplars in Global Health initiative, should prompt health officials around the world to push for multi-sectoral strategies that include both direct and indirect interventions to improve nutrition broadly and stunting in particular. Our research indicates that countries’ efforts to reduce stunting will stall if they are not employing both of these levers.

Consider the powerful forces we observed boosting nutrition in Ethiopia. Our quantitative and qualitative analyses found that– more than any other intervention – agricultural policies and programs drove the largest gains in Ethiopia’s stunting reduction through improved crop yields and, consequently, household food security. Other key drivers of stunting reduction in Ethiopia were also indirect interventions – better access to education, particularly for girls, and improvements to WASH – especially a reduction in open defecation – which drove 17 percent of the reduction in stunting.

While many recent high-quality randomized controlled trials suggest caution around WASH as a tool to address stunting, our research shows meaningful contributions of WASH improvements to stunting reduction in four of the five countries studied (Ethiopia, Nepal, Peru and Senegal). And this points to the value of our methodology. While randomized controlled trials are, without a doubt, an important tool in evaluating cause and effect, for reasons that remain unclear, they have not been able to effectively capture the impact of WASH programs on nutrition. We hope our research demonstrates the value of WASH programming and provides the necessary evidence to support further investment.

Lastly, outside our purview, but worth mentioning is that each of the indirect interventions I’ve highlighted here, improvements to WASH, education, and agriculture interventions like increasing access to agricultural extension agents, better quality fertilizer, and improved seeds, have substantial knock-on effects that support progress toward other, non-nutrition related global goals. They increase incomes, make agriculture more sustainable, keep girls in school, reduce un-wanted pregnancies, and reduce the spread of disease. These multiple benefits should be considered when governments are calculating the return on investment for all of the indirect interventions, from girls’ education and women’s empowerment, to WASH and agricultural extension agents.

We hope that this evidence, which is available in full on the Exemplars in Global Health platform here, persuades health leaders around the world to work across sectors to develop powerful multi-sectoral strategies to reducing stunting, which still impacts 149 million children around the world today.

Dr. Emily C. Keats is a Senior Research Associate at the SickKids Centre for Global Child Health in Toronto, Canada.

by Dr. Emily Keats

Exemplars in Global Health: A Tool to Help Achieve Progress on Maternal Anemia

Five years ago, building on the Millennium Development Goals, the United Nations set the Sustainable Development Goals (SDGs), 17 global targets for the world to meet and in doing so, “achieve a better and more sustainable future” for all by 2030.

To spur action to address all forms of malnutrition, SDG 2 was created, highlighting child wasting and overweight – the double burden of malnutrition. And in 2020, a critical addition addressing the nutritional needs of women of reproductive age was made (SDG 2.2).

Maternal anemia – which affects 40 percent of all pregnant women globally, and disproportionately affects those in low-income countries – became an important part of SDG 2, with a key indicator being a 50 percent reduction in women of reproductive age (15-49) with anemia by the year 2030, as compared to the baseline level registered in 2012.

Anemia is a condition in which the absolute number of red blood cells or their hemoglobin content is reduced, affecting their oxygen carrying capacity. Whether it’s non-nutritional anemia (caused by postpartum hemorrhage, heavy menstrual bleeding, infections like malaria or hookworm, and others), anemia caused by genetic disorders (thalassemia, glucose-6-phosphate dehydrogenase deficiency, and others), or nutritional anemia (caused by deficiencies in iron, vitamins, folic acid, riboflavin, and others), the disorder poses increased risk for women during pregnancy.

Therein lies a particular challenge. A pregnant woman’s total blood volume can increase (usually around 50 percent) over the course of her gestation. This means women – who are already prone to anemia – are at increased risk of developing it when they are pregnant, in part because their iron supplies do not automatically increase with their rise in blood volume. With 40 percent of pregnant women – and one-third of women of reproductive age – being anemic worldwide, this increases their risk of having low birth weight babies, premature birth and maternal mortality. In addition, maternal anemia carries an increased risk of adverse newborn and childhood outcomes, with cascading effects into adulthood.

With less than ten years to achieve SDG 2.2, the stakes are high and the arduous path to achieving progress on maternal anemia will require facing several issues:

First, we still lack a comprehensive understanding of the epidemiology of maternal anemia. Not only because it is a disorder that can result from multiple causes and/or diseases, but because globally, the etiology of anemia differs substantially across regions of the world. Standards that account for what is an acceptable hemoglobin level differ across factors, such as pregnancy status, age and sex, or environmental factors, like altitude and smoking (these standards are currently under review by the WHO). Further compounding this are drivers like inflammation or genetic factors, which impact hemoglobin levels, but are often not measured or accounted for.

Second, tracking anemia, especially among vulnerable populations (like the poorest women of South Asia and Central and West Africa) only takes place via surveys that occur every four to five years, and may not paint the whole picture. The data on the correlation between anemia and nutrition program coverage or population compliance is lacking, making it hard to implement interventions that would help improve access to iron and nutrition programs.

Third, because anemia is multi-factorial and its exact drivers (ranging from malnutrition to economic inequity to water and sanitation to access to education) are hard to pinpoint within most given geographic regions, adequate solutions are not in place for most women.

Finally, nutrition supplementation guidelines for pre-pregnant and pregnant women have not changed substantially, and are mainly based on the distribution of iron folic acid (IFA) supplements, even though the use of multiple micronutrient supplement (MMS) is now recommended in the context of rigorous research.

When a challenge is so prevalent and its solution so complex, a unique kind of perfect storm tends to brew. We’re seeing that, in many ways, with COVID-19. But with disorders like anemia, that have long affected the poorest in the world – and especially the poorest women in the world – a renewed commitment must be made to tackle this problem.

The 2020 addition of maternal anemia to the SDGs was an important step to highlight both the magnitude of the problem and the focus that experts in the public health community know it demands.

And today, those experts can use this platform, Exemplars in Global Health, to learn what makes specific public health interventions successful.

In the case of anemia, EGH is working to highlight certain countries, policies, and programs that have been effective in reducing anemia prevalence among women of reproductive age, analyzing why they’ve worked, and exploring what difficulties they’ve faced. EGH researchers are also examining how programs have been implemented and where they have been successful by analyzing the results that have been delivered, so solutions can be replicated.

Meeting SDG 2.2 will involve the work of many and an unrelenting pursuit by governments, civil society and public health experts, but having a blueprint of proven success ameliorates the challenge, improving the chances that we will get closer to achieving progress in maternal anemia by 2030.

For us, this is good news. Extraordinary progress can be inspirational, and even aspirational. But it is perhaps most useful when it is informative. If we are to address the problem of maternal anemia, we can now do so using the lessons of those who have achieved great success and whose victories we can build upon.

Authors: Francesco Branca, Zulfiqar A. Bhutta, Aatekah Owais

by Exemplars in Maternal Anemia Reduction Partnership

How does vaccine coverage impact stunting? Was it a key factor in any of the stunting exemplar countries?

Research on the impact of immunizations on stunting rates have suffered from an inability to isolate the impact of immunizations from the impact of a wide variety of other factors which may impact stunting rates including mother’s education, poverty rates etc.

This challenge stems from the fact that it would be unethical to conduct a randomized control trial (RCT) that provides vaccinations to some children and a placebo to others and then measure stunting rates, as the placebos would elevate childhood mortality rates.

Without RCT’s, we can assess the impact of vaccinations only through observation, and this research has thus far been somewhat inconclusive, with some small reduction of stunting detected in certain, but not all, geographies.

The ideal way to answer this question would be for growth in early childhood be an outcome of placebo-controlled vaccine efficacy trials. Such trials are designed to determine if there is an effect on an infectious disease outcome and have not included growth or development of stunting as an outcome. For example, the Cochrane Review of trials of vaccines for the prevention of rotavirus diarrhea, the most important cause of severe acute diarrhea in LMIC, did not include a growth outcome for any of the trials.1 Therefore, it is necessary to address this question using observational data, either from longitudinal surveillance or surveys, while dealing with the limitations of such data for causal inference.

A common type of published analysis is to examine the correlation between vaccine coverage and prevalence of stunting, defined as the child having a length/height-for-age more than two standard deviations lower than the median length/height-for-age of an international reference population. An example is an analysis of data from an Indonesian nutritional surveillance system.2 Partial- or non-receipt of three doses each of oral polio vaccine and DPT vaccine and measles vaccine was associated with increased stunting. However, there are several confounding challenges with this study; non-receipt of immunizations was associated with maternal age, education, income and distance to the health post. These factors may be associated with stunting independent of immunizations, and failure to control for them in the analysis means that there cannot be a causal inference regarding immunizations and stunting. When there are factors that are associated both with the exposure of interest, in this case immunizations, and with the outcome i.e. stunting this is referred to as confounding.

Other analyses have attempted to control for this possibility in various ways, often unsuccessfully, including a survey of several villages in Kenya.3 A logistic regression was used to assess a number of dietary and health service exposures, controlling for age, sex and a socio-economic status (SES), which was based on the agricultural resources of the household. In this analysis, children without up-to-date immunizations were more than twice as likely to be stunted than children with current immunizations. While their measure of SES was not associated with immunization status, other SES factors such as maternal education that were not included in the regression analysis, may have been, resulting in residual confounding.

Still other analyses have attempted to reduce the possible effect of confounding using more advanced statistical methods including an analysis of the effect of measles vaccination on child growth which used data from Demographic and Health Surveys from 65 LMIC.4 For causal inference, the authors used conditional logistic regression models with stunting at 12-59 months of age as the outcome to determine the effect of measles vaccination. The regression models used household and mother fixed effects that allowed comparison across siblings, controlling for observed and non-observed household confounders, and also controlled for a number of other characteristics of the mother and child, including vaccination with DPT vaccine as an indicator of the likelihood of getting any immunizations. Measles vaccination decreased the probability of being stunted by 11.5%. The analysis found a gender interaction with an effect on measles vaccination reducing stunting in boys but not girls.

An analysis of longitudinal survey data from Ethiopia, India and Vietnam also looked for an effect of measles vaccine on stunting.5 Regression analysis used propensity score matching to control for systematic differences between children who were vaccinated for measles or not. Children at 7-8 years of age who had been vaccinated for measles in infancy in India had a slightly higher height-for-age (0.13 z-score) than unvaccinated children; no significant effect was found in Ethiopia or Vietnam. At 11-12 years of age, there were no significant effects on stunting in any of the countries. Using the same survey data for India, the effect of receiving Hemophilus influenzae type b vaccine in early childhood on stunting was analyzed using a similar propensity score matching approach.6 A small (0.17 and 0.22 z-score) positive effect on height-for-age was found for 11-12 and 14-15 year olds.

Finally, another type of analysis has tried to explain the changes in the prevalence of stunting in seven Sub-Saharan African countries, considering the changes in distal and proximate determinants between two DHS surveys between 2005 and 2014.7 In five of the seven countries, the proportion of children fully immunized increased, coinciding with a decline in the prevalence of stunting, but immunization status was not included in the decomposition analysis so there is no statistical basis for its effect on stunting.

Looking at our Exemplar countries, we – again – find mixed data on the role of immunizations in stunting reduction. In each country a multivariable hierarchical (distal, intermediate and proximate levels) model was used to examine the association of a broad set of possible determinants, including DPT3 and measles vaccinations, on mean height-for-age z-score change over time (generally 2000-2016/17). Two countries had substantial increases in coverage of DPT3 and measles vaccine.

In Senegal, DPT3 improvement in coverage of these vaccines was associated with 9% of the explainable change in stunting in the decomposition analysis. In Ethiopia, in spite of substantial improvement in vaccine coverage, there was no meaningful effect on stunting. Two countries, Peru and Nepal, had relatively high vaccine coverage (71/72%) at the beginning of the time period and modest improvements; in neither country did change in vaccine coverage explain any of the change in stunting. In Kyrgyz Republic the initial vaccine coverage was almost universal and declined by a few percentage points, so as would be expected did not have any association with change in stunting prevalence.8

In conclusion, in LMIC immunization coverage with a set of routine childhood vaccines or with measles or Hemophilus influenzae type b vaccines may provide some protection from stunting, but the small effect on height is not found in all settings and may not persist to mid-childhood. The observational nature of the data available, even with the best statistical methods, has limitations for causal inference and results may still be influenced by residual confounding making small effects, even if statistically significant, questionable.

In the absence of rigorous vaccine-efficacy trials that measure childhood stunting or linear growth as an outcome, the current state of evidence is inconclusive.

Authored by: Dr. Robert Black, Chair, Department of International Health, Johns Hopkins University Link to Bio

1. Soares-Weiser K, Bergman H, Henschke N, Pitan F, Cunliffe N. Vaccines for preventing rotavirus diarrhoea: vaccines in use. Cochrane Database Syst Rev 2019; 2019(10).
2. Semba RD, De Pee S, Berger SG, Martini E, Ricks MO, Bloem MW. Malnutrition and infectious disease morbidity among children missed by the childhood immunization program in Indonesia. Southeast Asian Journal of Tropical Medicine and Public Health 2007; 38(1): 120.
3. Bloss E, Wainaina F, Bailey RC. Prevalence and predictors of underweight, stunting, and wasting among children aged 5 and under in western Kenya. J Trop Pediatr 2004; 50(5): 260-70.
4. Bogler L, Jantos N, Bärnighausen T, Vollmer S. Estimating the effect of measles vaccination on child growth using 191 DHS from 65 low-and middle-income countries. Vaccine 2019; 37(35): 5073-88.
5. Nandi A, Shet A, Behrman JR, Black MM, Bloom DE, Laxminarayan R. Anthropometric, cognitive, and schooling benefits of measles vaccination: Longitudinal cohort analysis in Ethiopia, India, and Vietnam. Vaccine 2019; 37(31): 4336-43.
6. Nandi A, Deolalikar AB, Bloom DE, Laxminarayan R. Haemophilus influenzae type b vaccination and anthropometric, cognitive, and schooling outcomes among Indian children. Ann N Y Acad Sci 2019; 1449(1): 70-82.
7. Buisman LR, Van de Poel E, O'Donnell O, van Doorslaer EK. What explains the fall in child stunting in Sub-Saharan Africa? SSM-population health 2019; 8: 100384.
8. Results provided by N Akseer, Z Bhutta.

by Robert Black

How should  policy-makers  think about whether to invest in nutrition sensitive or nutrition specific interventions? What is the relative contribution of each in reducing stunting rates?

One of the challenging things about addressing stunting is the complex web of factors that contribute to the condition. There is no silver-bullet solution, because there is no single cause of chronic undernutrition.

To help us think systematically about how to tackle this complexity, we’ve talked in recent years in terms of nutrition-specific and nutrition-sensitive interventions. Nutrition-specific interventions relate to the immediate determinants of growth and development, such as breastfeeding, complementary feeding and micronutrient intake, for example. Nutrition-sensitive interventions, on the other hand, relate to underlying determinants, such as basic food security, health interventions and education. Now we’re updating the framework slightly, and we’re thinking in terms of direct and indirect interventions (which more or less map to nutrition-specific and nutrition-sensitive) in the health and non-health sectors. Even using this mental model, it can be difficult to determine how much effect a given intervention is having, because data limitations mean we have to use proxy indicators, especially when it comes to direct interventions which are usually delivered through from the health sector and solid quantification of quality of diets.

That said, the analysis from Exemplars in Global Health (EGH) may be pointing to a bit of a shift in our thinking: In the past, we believed that about two thirds of the key interventions happened inside the health sector, and about one third happened outside of it. There are indications in the countries where the EGH research was carried out that the split may be closer to 50/50. On average, about half the successful interventions in our Exemplar countries came from a non-health sector. (It is important to note, though, that the 50/50 split I mentioned is an average across the countries we’ve studied. Each country’s experience is unique.)

The EGH analyses suggest two things. First, direct interventions are “non-negotiable.” In every case, they account for a significant portion of the impact the EGH program studied. Second, non-health sectors may play a more important role than we knew, and we should keep pushing ourselves to collaborate across traditional sectoral boundaries and expand the evidence base of what works and how to take it to scale.

The reality is that financial resources are rarely truly fungible across sectors, so it is much more of a question of how to best shape investments in sectors that can provide direct and indirect interventions. It is essential to design interventions properly, whether direct or indirect, health or non-health. That means targeting them to the specific geographies, age groups, or socio-economic groups that are most at risk. And it means delivering services with high enough coverage and fidelity to have the desired impact.

Authored by: Shawn Baker, Chief Nutritionist, USAID Link to bio

by Shawn Baker

What was the role of cash transfers in reducing stunting in Exemplar countries?

The impact of conditional cash transfer program in Peru (Juntos) as a stand-alone intervention on under-5 stunting, has not been conclusively demonstrated.
Different studies with different methodologic designs have been conducted to assess the impact of Juntos, and the results have shown little or no effect on under-5 stunting, although the effect on severe stunting tended to be more evident. Read more here.

More recently, my team conducted two studies using DHS as the main source of information. In the first one, through an ecological analysis conducted at departmental level through a multilevel mixed-effects linear regression, we found that a combination of factors accounted for the reduction in under-5 stunting from 2000 to 2012, with social determinants and out-of-health changes contributing more than proximal factors.1 In another study assessing the period 2000-2016, which included the mixed-effects linear regression and a decomposition analysis, we found that Juntos implementation had a significant association with stunting prevalence for the period 2000-2016. (Submitted).

In Peru, Juntos was aimed at reaching the poorest families. It was introduced in 2005 and scaled up quickly, reaching most of the country’s poor rural families. To receive a cash payment of USD 33 per month, mothers needed to access specific preventive and curative health services for themselves and their children on an ambitious schedule. For the complete list of Juntos requirements, read more here.

The available evidence suggests that conditional cash transfer programs like Juntos can impact the longitudinal growth of children by contributing to the reduction of poverty, increasing women's empowerment and reducing fertility rate, consequently allowing for better care and nutritional status of children. The Juntos program itself was not a specific driver of stunting reduction. Rather, it was a powerful enabler, contributing to a series of holistic investments across several sectors that collectively drove down stunting.

Likewise, in Kyrgyzstan during the post-independence period, the government maintained a small but well-targeted cash transfer program that, despite its size, put cash in the hands of families that needed it. The Universal Monthly Benefit (link) initially covered about ten percent of the population. It provided the poorest families with children between the ages of 18 months and 16 years with a grant of about 50 soms, or less than $1 per month. By targeting the poorest families with children, it reached children most at risk of stunting.

Authored by: Dr. Luis Huicho, Director, Center for Research in Maternal and Child Health; Director of Research, Research Center for Integral and Sustainable Development, Universidad Peruana Cayetano Heredia, Lima, Peru Link to Bio

1  Sánchez A, Jaramillo M. Impacto del programa Juntos sobre nutrición temprana. Work Pap Ser [Internet]. 2012; Available from: https://ideas.repec.org/p/gad/doctra/dt61.html
2  Perova E, Vakis R. Welfare impacts of the “Juntos” Program in Peru; Evidence from a non-experimental evalaution [Internet]. 2009 [cited 2019 Apr 25]. Available from: http:www2.juntos.gob.pe/modulos/mod_legal/archivos/Evaluacion_Cuasi-Experimental1.pdf
3  Huicho L, Huayanay-Espinoza CA, Herrera-Perez E, Segura ER, Niño de Guzman J, Rivera-Ch M, Barros AJ. Factors behind the success story of under-five stunting in Peru: a district ecological multilevel analysis. BMC Pediatr. 2017 Jan 19;17(1):29. doi: 10.1186/s12887-017-0790-3.

by Luis Huicho

How important are investments in Water, Sanitation, and Hygiene in reducing stunting across Exemplar countries? How does the observed impact in Exemplar countries relate to the recent mixed RCT results?

The question as to whether investments in water, sanitation and hygiene (WASH) impacts nutrition outcomes, especially linear growth, has vexed researchers for a very long time.

The classic association of poor WASH conditions with high burdens of disease –especially diarrheal disorders – is well-recognized. For a long time the pathway to linear growth deceleration and stunting was thought to be due to repeated diarrheal episodes with associated nutrition penalty.

Careful longitudinal studies, however, determined that short duration diarrheal episodes usually did not lead to linear growth deceleration nor were diarrheal disease burdens clearly associated with stunting unless the episodes were prolonged or persistent. While several observational studies include ecological analyses of linear growth within DHS data sets (Speers et al, several analyses1) indicated that stunting was associated with poor WASH status, especially hygiene and sanitation, corresponding data from randomized trials and systematic reviews have been confusing to say the least. Despite this uncertainty, WASH interventions have remained a sacrosanct part of “nutrition sensitive” or indirect interventions outside of the health sector.

More recent cohort studies such as MalED2 also confirm the association of impaired linear growth with high burden of bacterial colonisation in the gut and possible “environmental enteric dysfunction”, an important features of early growth failure.

However, Dangour et al conducted a Cochrane review of available information from WASH trials in 2013 and concluded that the effect on linear growth was small.

More recently, two large cluster RCTs of WASH (and additional nutrition interventions) in Bangladesh, Kenya and Zimbabwe (Luby et al and Humphreys et al 2018/20193) failed to show any impact on linear growth in children under 5, again throwing open the question of the link between WASH and linear growth.

These findings from carefully conducted RCTs must however be considered with caution as they may not capture the full, “real life” benefits of WASH on health and nutrition that occur at scale and over time. To illustrate, the SHINE and WASH benefits investigators themselves recognize that the effect of such interventions may well relate to the quality of intervention and dose exposure.

An alternative means of assessing the potential relationship of WASH investments on linear growth might be from ecological studies in countries which have made progress across several domains (social determinants, education, female empowerment and economic development). Indeed, our Stunting Exemplars research suggests a clearer connection. In countries with poor baseline WASH and environmental conditions, especially sanitation, we are able to see the independent impact of WASH investments on linear growth (in addition to improved health and nutrition investments and those related to socioeconomic growth, food security and education). This provides further evidence to support investments in safe water, sanitary conditions, and personal hygiene measures as a cornerstone for improved health and nutrition outcomes.

Our overall analysis does suggest that benefits from WASH investments accrue across a range of outcomes, including linear growth and importantly influencing overall nutrition and human development outcomes. Additionally, looking beyond implications for linear growth alone, countries will continue to invest in clean, safe water, proper sanitation, and promotion of hygienic measures as a fundamental human right.

Authored by: Dr. Zulfiqar Bhutta, Co-director of the Center for Global Child Health, The Hospital for Sick Children, Toronto Link to Bio


1 Geruso, M., & Spears, D. (2018). Neighborhood sanitation and infant mortality. American Economic Journal: Applied Economics, 10(2), 125–162; Spears, D. (2013a). How much international variation in child height can sanitation explain? (Working paper). Princeton, NJ: Princeton University; Spears, D. (2013b). Policy lessons from the implementation of India’s total sanitation campaign. India Policy Forum, 9, 63–99.
2 Murray-Kolb LE, Rasmussen ZA, Scharf RJ, et al. The MAL-ED cohort study: methods and lessons learned when assessing early child development and caregiving mediators in infants and young children in 8 low- and middle-income countries. Clin Infect Dis. 2014;59 Suppl 4(Suppl 4):S261–S272. doi:10.1093/cid/ciu437
3 Luby SP, Rahman M, Arnold BF, et al. Effects of water quality, sanitation, handwashing, and nutritional interventions on diarrhoea and child growth in rural Bangladesh: a cluster randomised controlled trial. The Lancet Global Health. 2018;6(3). doi:10.1016/s2214-109x(17)30490-4

by Zulfiqar Bhutta