Change: Creating a Poverty Grading System at the Marie Stopes Clinic Society

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Case Study by Seth Kahan

Written for Johns Hopkins Bloomberg School of Public Health Center for Communication Programs

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The Marie Stopes Clinic Society (MSCS), part of the Marie Stopes International Partnership, was established in 1988 in Chittagong, Bangladesh, to provide sexual and reproductive health care and education. Since it began, MSCS has grown to include 23 comprehensive health clinics throughout the nation and an additional 46 “mini-centers” in urban slums. MSCS offerings include family planning education and services; ante- and post-natal care; female sterilization; vasectomy; primary health care; youth services; prevention, diagnosis, and treatment of sexually transmitted infections; and STI/HIV/AIDS awareness-raising initiatives.

As the population and reproductive health indicators in the box suggest, MSCS’s education and services are needed. Bangladesh’s population growth and total fertility rates remain high, despite an increase in the use of contraceptives from 45 percent in 1994 to 54 percent in 2000 (60). Infant and maternal mortality also pose a challenge, as do other reproductive health problems.

MSCS recognizes that poverty causes poor sexual and reproductive health, and vice versa. Therefore the organization seeks to reach the very poor, who are most in need of services. Tanya Huq Shahriar, Knowledge and Social Development Manager of MSCS, reports: “Around 80,000 clients per month come to our clinics and mini-centers. They are urban poor and vulnerable. This includes the homeless, young people and women of slums and shanty towns, sex workers, drug users, men having sex with men, factory workers, etc.”

Dr. Yasmin Ahmed, Managing Director of MSCS, says: “We have developed several innovative programs to reach and serve. We hope these programs will reach the poorest of the poor. There are many obstacles to reaching them, but the first challenge is to identify them. This is not easy. There is so much to consider, and not all is obvious to the outsider.”

Identifying the Very Poor

International and national definitions of poverty often fall short of identifying those most in need of care, because they do not take situational nuances and circumstances into consideration. For example, income conventionally has been used as a measure of poverty, and households falling beneath a certain threshold level have been considered poor. Yet a family may have an income level higher than the defined threshold but be pushed into poverty by other factors, such as a large number of dependents or a major illness in the family. Thus a more holistic approach is needed to identify very poor households. Determining which factors should be taken into consideration is a difficult task. Dr. Ahmed, Ms. Shahriar, and their team designed a strategy in which they turned to the poor for answers.

Ahmed explains: “When it comes to extreme poverty in slums, it varies so much and there is no one criterion which you can use to measure. So we looked at the research. Some sources use income, some use household access. Each was right in its own way, but none captured the whole spectrum of poverty. That is why we decided to go back to the community and actually ask them to grade their own poverty.”

BANGLADESH:

POPULATION AND REPRODUCTIVE HEALTH INDICATORS

Total population, 2004. . . . . . . . . . . . . . . . . . . . . . . . . . . 149.7 million

Projected population, 2050 . . . . . . . . . . . . . . . . . . . . . . 254.6 million

Life expectancy (male/female) . . . . . . . . . . . . . . . . 61.0 / 61.8 years

Contraceptive prevalence: any method . . . . . . . . . . . . . 54 percent

Contraceptive prevalence: modern methods. . . . . . . . . 43 percent

Births per 1,000 women ages 15-49. . . . . . . . 117 per 1,000 women

Maternal mortality ratio . . . . . . . . . . . . . 380 per 100,000 live births

Infant mortality rate. . . . . . . . . . . . . . . . . . . . 64 per 1,000 live births

Average annual population growth rate, 2000-2005 . . 2.0 percent

Total fertility rate, 2000-2005 . . . . . . . . . . . . . . . . . . . . 3.46 children

Births with skilled attendants . . . . . . . . . . . . . . . . . . . . . 12 percent

Health expenditures, public . . . . . . . . . . . . . . . 1.5 percent of GNP

Source: UNFPA, 2004

Participatory Knowledge Development

Those closest to a situation generally have the richest and most relevant knowledge. Ahmed points out: “We used volunteers who were actually members from the same slum. We said, ‘You go ahead and grade households according to whatever you think would be the criteria. Just remember to note why you categorized each household as you did.’ We sent our volunteers out … to all the houses in the slums. They categorized them into four groups. Then we had a debriefing session with them.

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