Data quality in demographic surveys: tests and experiments

Different surveys were giving different results about malnutrition of young children. The objective of this paper are: (i) to assess the quality of anthropometric and age data of children of the Multiple Cluster Indicator Survey (MICS) of Somalia 2006, and (ii) to identify the sources of errors and (iii) to suggest recommendations for improving data. Consistency checking of the indices, deviation from the expected pattern of age distribution, age specific malnutrition, and distribution of digits of weight and height were used as measuring tools of errors. Some qualitative data were collected by interviewing key survey persons and checking the filled in questionnaire and data files. National Nutrition Survey (NNS) and DHS data were used for comparison. Some errors in weight and height data were present. But mainly error in age makes the estimate of malnutrition unexpectedly high. Different sources of errors were identified. Error in age, weight and height data need serious attention to make estimate of malnutrition meaningful. Good training, supervision, and equipment are essential for obtaining good quality weight and height data. In addition to all of these, necessary methods and tools including a calendar of local events should be developed, tested and used for good age data.

According to census data,the TFR in China was 1.18 in 2010,which activated the discussion of census data quality and the real fertility level in China.It is necessary to figure out how credible are recent census data,especially the fertility data,which are the fundamental index of population and important factor closely related to the public policies.This paper focuses on assessing the fertility data quality in China’s recent censuses and methods of improving it. The household registration data and educational statistics,which are independent of census system,were used to research whether there was underreporting in census data and improve the quality of it.The results suggested there was underreporting in census data, especially in the low-age groups.The data quality of educational statistics is the best because the number of children in the educational statistics has no close relationship with the interest of local governments and reporters,which is quite different from census data.So we combined the tendency of census data and the fertility level of education statistical data to correct the missing reports in the census data both in direct and indirect method to make improvements for the quality of census data,especially the low-age group data.Finally,the estimated TFR after emendation is listed at the end of this paper.

Age is one of the most basic and important information collected in almost all demographic and health surveys. Most of the demographic researches on fertility, reproductive health and contraception focus on females of particular age group who are in their reproductive period. Important demographic indicators like fertility, contraception and mortality are estimated on the basis of reporting of the female respondents. This particular study makes an attempt in exploring the degree of matching and mismatch and its spatial variation in reporting of the age of the husbands by the wives in India. Multivariate analysis has been used to find the causal relationship beteen various socio-economic-demographic background and the mismatch in reporting of age of the husband. The present study analyses the concordance and discordance of the reporting of the husband's age as reported by the wife and by the husband separately by using a nationally representative sample size of 42185 couples. It is found that in India about three fifth of the cases (58 percent), there is mismatch(discordance) in reporting of husband's age as reported by the wife and the husband.

According to household surveys, some 4% of inhabitants in France ‘usually’ live in more than one dwelling. Previous studies have shown that having more than one “usual” dwelling is the most common among young adults, who have left their parental home but are still “usually living with their parents”. Having two homes regularly increases with age for children, as parental couples experience separation. Very rare around age 30, multiple residence increases up to retirement age for adults, reaching a second mode at ages 55-85.

Focusing on adults, the present paper will describe the family situation and working status of two-home adults. Concerning couples around retirement age, two assumptions will be discussed: first, the case where both members of couples are commuting together between two “usual residences”, the former holiday home becoming a second usual residence. Second, while having more than one home is a transitory situation at younger ages, this situation is more stable around retirement age. These assumptions will be checked using two new French datasets, the “Family and Dwellings” survey, a one percent survey which took place within the 2011 census, and a dataset gathering a collection of household surveys including the same set of questions on multiple residence.

Short Abstract: Age is an important variable in the anthropometric investigation of nutritional status of children. Bias and random error are common in children’s age data. We assess the effect of bias and random error in age on (i) estimates of malnutrition; and on (ii) the mortality discriminating power of age dependent anthropometric indicators. Accurate age, weight, height and mortality data were collected for 1,571 Bangladeshi children under five years of age. We introduce systematic bias and random error into the age variable and compute anthropometric indicators using both the correct original data and the data with errors. Results from different data sets are compared. Positive age bias over estimates while negative bias under estimates malnutrition. It is shown statistically and empirically in the paper that if malnutrition in the population is less than 50%, random error in age overestimates malnutrition; if it is more than 50%, it underestimates malnutrition; and if it is 50%, there will be no effect. Both bias and random error affect the mortality discriminating power of anthropometric indices. Errors in age data of young children deserve serious attention to make anthropometric investigation of young children meaningful and useful.

The experience of it in different states of India are diverge we have identified 14 states that has indication of fertility stalling. The specific objective are
Reconstructions of fertility trends adjusting omission and displacements using birth history of 14 Indian states
Identify true and spurious stalls in different states by fitting autoregressive-dummy variable regression
Propose a suitable model for forecasting TFR using using Box-Jenkins methodology.
We have pooled three rounds of DHS birth history files and converted it to “person period” files to apply Poisson regression model to arrive at the long terms fertility trend adjusted for displacement and omission (Schoumker, 2008).
Ln(mi)=ln(t) +f(age) + g(time)+ O(i)+DB(i)+DA(i); where i=1, 2, 3 three rounds of DHS.
We have applied dummy variable regression with autoregressive component to identify stall period
〖TFR〗_t=α_0+α_1 〖TFR〗_(t-2) +α_(2 ) D_( t )+α_3 〖(D〗_( t ) 〖TFR〗_(t-2) )+∪_t
Finally, the ARIMA (p, q, r) model is used for projecting the future level of fertility. The model suggests that the current as well as forecasted value of TFR is substantially higher than the projected TFR by the Technical Group.
The policy implication that may lead to lack of adequate focus on family planning program is also assed in the paper.

Abstract: The International Conference on Population and Development (ICPD) in 1994 signaled a major breakthrough in the way governments and health professionals think about the reproductive health. Data on currently married women aged 15-49 from the 2011 Ethiopian Demographic and Health Survey were analyzed to correlate fertility decline rate and health matters. Findings show that 67 percent of population has access to any type of potential health services. In Ethiopia total fertility rate is 4.8 births per women in 2011. The maternal mortality rate, 676 per 100,000 live births and the infant mortality rate at 56 per 1,000 live births are among the highest in the world. Only 34 percent of women receive antenatal care and skilled personnel attend only 8 percent of births. Even though associations were not consistent across all indicators, spousal discussion of family planning was linked to an increased likelihood of receiving skilled antenatal care, delivery care and health services. Postnatal care is extremely low in Ethiopia. Low status of women in Ethiopia underpins and often directly undermines utilization of reproductive health services. The reproductive health care is the major issue which determines the demographic goals of any couple.

Our study purpose is to assess data quality of self-reported current use of the Lactational Amenorrhea Method (LAM) in the Demographic and Health Surveys (DHS). LAM, an important contraceptive method during the postpartum period, is a modern contraceptive with an effectiveness rate of 98% for the six month postpartum period when used correctly. Our study’s specific objectives are: 1) to examine accuracy of self-reported LAM use compared to the constructed correct practice variable, and 2) to explore differentials in accuracy measures by characteristics at the individual-level and survey-level by analyzing data from 73 DHS conducted in 45 countries since 1998. Findings reveal that on average only 26% of reported LAM users met criteria of correct LAM practice across the surveys, indicating potentially unacceptably low user effectiveness at the population level. We discuss implications for future DHS data collection efforts, and implications for family planning and maternal and child health programming.

Data on children in the MENA region is limited and aggregated at the country level and what is available at the lower levels is mostly fragmented, defective and incomplete. This hinders creation of databases and identification of the appropriate indicators. The situation becomes worse when talking about data on urban children.

This paper will identify the data gaps and propose the minimum required sets of indicators, particularly those relating to public and basic services, including education, health, nutrition, social phenomena such as child-labor, street children, and Juvenile delinquencies. The paper will develop an analytical framework to illustrate the types of data required from household surveys & censuses at the local authorities level to provide health & socio-economic indicators for children. The framework will consider the geographical context in which the household and the local communities are located.
The paper will propose other suitable methods to collect basic data or to supplement with more detailed data; these methods could be resorted to, in order to minimize time and cost, keeping precision and accuracy,
The paper will identify the responsible partners and will conclude with recommendations for interventions to strengthen the knowledge base capabilities regarding children in local authorities.

Nigeria’s census history began in 1866; during the intervening period to date, Nigeria has had 12 censuses. Using age in single years, the census data were subjected to tests of quality by using known quality tests available. The quality of Nigeria’s most recent censuses (1991 and 2006) was assessed using the following indices to assess the extent of errors: sex and age ratios, UN joint score, Whipple’s index, modified Whipple’s index, Myers’ index and index preference. The results of these assessment showed that the quality of the censuses data are comparable to some African censuses results obtained in the 1970s and 1980s. It is thus concluded that the quality Nigeria’s age and sex data were poor.