A Dynamic Three-Dimensional Air Pollution Exposure Model for Hong Kong.

INTRODUCTION: High-density high-rise cities have become a more prominent feature globally. Air quality is a significant public health risk in many of these cities. There is a need to better understand the extent to which vertical variation in air pollution and population mobility in such cities affect exposure and exposure-response relationships in epidemiological studies. METHODS: We used a novel strategy to execute a staged model development that incorporated horizontal and vertical pollutant dispersion, building infiltration, and population mobility patterns in estimating traffic-related air pollution (TRAP) exposures in the Hong Kong Special Administrative Region (HK SAR).Two street-level spatial monitoring campaigns were undertaken to facilitate the creation of a two-dimensional land-use regression (LUR) model. A network of approximately 100 passive nitric oxide-nitrogen dioxide (NO-NO2) monitors was deployed for two-week periods during the cool and warm seasons. Sampling locations were selected based on population and road network density with a range of physical and geographical characteristics represented. Eight sets of portable monitors for black carbon (BC) and particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) were rotated so as to be deployed at 80 locations for a 24-hour period. Land-use, geographical, and emissions layers were combined with the spatial monitoring campaign results to create spatiotemporal exposure models.Vertical air pollution monitoring was carried out at six strategic locations for two weeks in the warm season and two weeks in the cool season. Continuous measurements were carried out at four different heights of a residential building and on both sides of a street canyon. The heights ranged from as close to street level as practically possible up to a maximum of 50 meters (i.e., below the 20th floor). Paired indoor monitoring was included to allow the calculation of infiltration coefficients to feed into the dynamic component of the exposure model.The final phase of model development addressed population mobility. A population-representative travel behavior survey (n = 89,358) was used to produce the dynamic component of the model, with time-weighted exposure estimates split between home and work or school. Transport microenvironment exposures were taken from published literature. Time-activity exposure estimates were split by age, sex, and employment status.Development of the exposure model in distinct packages allowed the application of a staged approach to an existing cohort data set. Mortality risk estimates for an elderly cohort of 66,000 Hong Kong residents were calculated using increasing exposure model complexity. RESULTS: The street-level (2-dimensional [2D]) LUR modeling captured important spatial parameters and represented spatial patterns of air quality in Hong Kong that were consistent with the literature. Higher concentrations of gaseous pollutants were centered in Kowloon and the northern region of Hong Kong Island. PM2.5 and BC predictions exhibited a north-south/west-east gradient, with higher concentrations in the northwest due to regional transport of particulate pollutants from Mainland China. While the degree of explained variance of the models was in line with other LUR modeling efforts in Asia, R2 values ranged from 0.46 (NO2) to 0.59 (PM2.5).Exponential decay rates (k) were calculated at each monitoring location. While it was clear that k values were higher during the warm season than the cool season, no robust patterns were identified relating to the canyon physical parameters. Therefore, a single decay rate was used for each pollutant across the whole region for derivation of the 3-dimensional (3D) exposure layer (k = 0.004 and 0.012 for PM2.5 and BC, respectively). An alternative decay profile that capped decay at 20 meters above street level was proposed and evaluated. The electrochemical sensors deployed during the canyon campaigns did not exhibit the degree of interunit precision necessary to detect vertical variations in gaseous pollutants, and these results were excluded from the study.We found that values of the median infiltration efficiencies (Finf) for both BC and PM2.5 were especially high during the cool season (91%). Finf values were somewhat lower during the warm season (81% and 88% for PM2.5 and BC, respectively), and we found a significant negative correlation between air conditioning use and Finf. The Finf for a mechanically ventilated office building was 45% and 40% during the cool and warm seasons, respectively.Dynamic exposure estimates were compared against home outdoor estimates. As expected, the addition of an indoor component decreased time-weighted exposure estimates, which were balanced out to some extent by the inclusion of transport microenvironments. Overall, mean time-weighted exposures for the full dynamic model were around 20% lower than home outdoor estimates.Higher levels of exposures were found with working adults and students than for those neither in work nor study. This was due to the increased mobility of people going to work or school. The exposures to PM2.5, BC, and NO2 were, respectively, 13%, 39%, and 14% higher for people who were under age 18, compared with people who were 65 or older. Exposure estimates for the female population were approximately 4% lower.The availability of an existing cohort data set of elderly Hong Kong residents (n = 66,820) facilitated the calculation and comparison of mortality risk estimates for the different exposure models.Overall, results indicated that the application of exposure estimates that incorporated infiltration, vertical, and to a lesser extent, dynamic components resulted in higher hazard ratios (HRs) than the standard street-level model and increased the number of significant associations with all-natural-cause, cardiovascular, and respiratory mortality outcomes. CONCLUSIONS: The results from the study provided the first evidence that considering air pollution exposure in a dynamic 3D landscape would benefit epidemiological studies. Higher HRs and a greater number of significant associations were found between mortality and pollutant exposures that would not have been found had standard 2D exposure models been used. Dynamic models can also identify differential exposures between population subtypes (e.g., students and working adults; those neither in work nor study).Improved urban building design appears to be stimulating the dispersion of local TRAP in street canyons. Conversely, Finf values found in naturally ventilated buildings were high, and residences provided little protection from ambient air pollution.We have demonstrated that the creation of effective advanced exposure models is possible in Asian cities without an undue burden on resources. We recommend that vertical exposure patterns be incorporated in future epidemiological studies in high-rise cities where the floor of residence is recorded in health record data.

Effects of short-term exposure to air pollution on hospital admissions of young children for acute lower respiratory infections in Ho Chi Minh City, Vietnam.

There is emerging evidence, largely from studies in Europe and North America, that economic deprivation increases the magnitude of morbidity and mortality related to air pollution. Two major reasons why this may be true are that the poor experience higher levels of exposure to air pollution, and they are more vulnerable to its effects--in other words, due to poorer nutrition, less access to medical care, and other factors, they experience more health impact per unit of exposure. The relations among health, air pollution, and poverty are likely to have important implications for public health and social policy, especially in areas such as the developing countries of Asia where air pollution levels are high and many live in poverty. The aims of this study were to estimate the effect of exposure to air pollution on hospital admissions of young children for acute lower respiratory infection (ALRI*) and to explore whether such effects differed between poor children and other children. ALRI, which comprises pneumonia and bronchiolitis, is the largest single cause of mortality among young children worldwide and is responsible for a substantial burden of disease among young children in developing countries. To the best of our knowledge, this is the first study of the health effects of air pollution in Ho Chi Minh City (HCMC), Vietnam. For these reasons, the results of this study have the potential to make an important contribution to the growing literature on the health effects of air pollution in Asia. The study focused on the short-term effects of daily average exposure to air pollutants on hospital admissions of children less than 5 years of age for ALRI, defined as pneumonia or bronchiolitis, in HCMC during 2003, 2004, and 2005. Admissions data were obtained from computerized records of Children's Hospital 1 and Children's Hospital 2 (CH1 and CH2) in HCMC. Nearly all children hospitalized for respiratory illnesses in the city are admitted to one of these two pediatric hospitals. Daily citywide 24-hour average concentrations of particulate matter (PM) < or =10 microm in aerodynamic diameter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2) and 8-hour maximum average concentrations of ozone (O3) were estimated from the HCMC Environmental Protection Agency (HEPA) ambient air quality monitoring network. Daily meteorologic information including temperature and relative humidity were collected from KTTV NB, the Southern Regional Hydro-Meteorological Center. An individual-level indicator of socioeconomic position (SEP) was based on the degree to which the patient was exempt from payment according to hospital financial records. A group-level indicator of SEP was based on estimates of poverty prevalence in the districts of HCMC in 2004, obtained from a poverty mapping project of the Institute of Economic Research in HCMC, in collaboration with the General Statistics Office of Vietnam and the World Bank. Poverty prevalence was defined using the poverty line set by the People's Committee of HCMC of 6 million Vietnamese dong (VND) annual income. Quartiles of district-level poverty prevalence were created based on poverty prevalence estimates for each district. Analyses were conducted using both time-series and case-crossover approaches. In the absence of measurement error, confounding, and other sources of bias, the two approaches were expected to provide estimates that differed only with regard to precision. For the time-series analyses, the unit of observation was daily counts of hospital admissions for ALRI. Poisson regression with smoothing functions for meteorologic variables and variables for seasonal and long-term trends was used. Case-crossover analyses were conducted using time-stratified selection of controls. Control days were every 7th day from the date of admission within the same month as admission. Large seasonal differences were observed in pollutant levels and hospital admission patterns during the investigation period for HCMC. Of the 15,717 ALRI admissions occurring within the study period, 60% occurred in the rainy season (May through October), with a peak in these admissions during July and August of each year. Average daily concentrations for PM10, O3, NO2, and SO2 were 73, 75, 22, and 22 microg/m3, respectively, with higher pollutant concentrations observed in the dry season (November through April) compared with the rainy season. As the time between onset of illness and hospital admission was thought to range from 1 to 6 days, it was not possible to specify a priori a single-day lag. We assessed results for single-day lags from lag 0 to lag 10, but emphasize results for an average of lag 1-6, since this best reflects the case reference period. Results were robust to differences in temperature lags with lag 0 and the average lag (1-6 days); results for lag 0 for temperature are presented. Results differed markedly when analyses were stratified by season, rather than simply adjusted for season. ALRI admissions were generally positively associated with ambient levels of PM10, NO2, and SO2 during the dry season (November-April), but not the rainy season (May-October). Positive associations between O3 and ALRI admissions were not observed in either season. We do not believe that exposure to air pollution could reduce the risk of ALRI in the rainy season and infer that these results could be driven by residual confounding present within the rainy season. The much lower correlation between NO2 and PM10 levels during the rainy season provides further evidence that these pollutants may not be accurate indicators of exposure to air pollution from combustion processes in the rainy season. Results were generally consistent across time-series and case-crossover analyses. In the dry season, risks for ALRI hospital admissions with average pollutant lag (1-6 days) were highest for NO2 and SO2 in the single-pollutant case-crossover analyses, with excess risks of 8.50% (95% CI, 0.80-16.79) and 5.85% (95% CI, 0.44-11.55) observed, respectively. NO2 and SO2 effects remained higher than PM10 effects in both the single-pollutant and two-pollutant models. The two-pollutant model indicated that NO2 confounded the PM10 and SO2 effects. For example, PM10 was weakly associated with an excess risk in the dry season of 1.25% (95% CI, -0.55 to 3.09); after adjusting for SO2 and O3, the risk estimate was reduced but remained elevated, with much wider confidence intervals; after adjusting for NO2, an excess risk was no longer observed. Though the effects seem to be driven by NO2, the statistical limitations of adequately addressing collinearity, given the high correlation between PM10 and NO2 (r = 0.78), limited our ability to clearly distinguish between PM10 and NO2 effects. In the rainy season, negative associations between PM10 and ALRI admissions were observed. No association with O3 was observed in the single-pollutant model, but O3 exposure was negatively associated with ALRI admissions in the two-pollutant model. There was little evidence of an association between NO2 and ALRI admissions. The single-pollutant estimate from the case-crossover analysis suggested a negative association between NO2 and ALRI admissions, but this effect was no longer apparent after adjustment for other pollutants. Although associations between SO2 and ALRI admissions were not observed in the rainy season, point estimates for the case-crossover analyses suggested negative associations, while time-series (Poisson regression) analyses suggested positive associations--an exception to the general consistency between case-crossover and time-series results. Results were robust to differences in seasonal classification. Inclusion of rainfall as a continuous variable and the seasonal reclassification of selected series of data did not influence results. No clear evidence of station-specific effects could be observed, since results for the different monitoring stations had overlapping confidence intervals. In the dry season, increased concentrations of NO2 and SO2 were associated with increased hospital admissions of young children for ALRI in HCMC. PM10 could also be associated with increased hospital admissions in the dry season, but the high correlation of 0.78 between PM10 and NO2 levels limits our ability to distinguish between PM10 and NO2 effects. Nevertheless, the results support the presence of an association between combustion-source pollution and increased ALRI admissions. There also appears to be evidence of uncontrolled negative confounding within the rainy season, with higher incidence of ALRI and lower pollutant concentrations overall. Exploratory analyses made using limited historical and regional data on monthly prevalence of respiratory syncytial virus (RSV) suggest that an unmeasured, time-varying confounder (RSV, in this case) could have, in an observational study like this one, created enough bias to reverse the observed effect estimates of pollutants in the rainy season. In addition, with virtually no RSV incidence in the dry season, these findings also lend some credibility to the notion that RSV could influence results primarily in the rainy season. Analyses were not able to identify differential effects by individual-level indicators of SEP, mainly due to the small number of children classified as poor based on information in the hospitals' financial records. Analyses assessing differences in effect by district-level indicator of SEP did not indicate a clear trend in risk across SEP quartiles, but there did appear to be a slightly higher risk among the residents of districts with the highest quartile of SEP. As these are the districts within the urban center of HCMC, results could be indicative of increased exposures for residents living within the city center. (ABSTRACT TRUNCATED)

Effect of influenza on cardiorespiratory and all-cause mortality in Hong Kong, Singapore and Guangzhou.

1. Using a common modelling approach, mortality attributable to influenza was higher in the two subtropical cities Guangzhou and Hong Kong than in the tropical city Singapore. 2. The virus activity appeared more synchronised in subtropical cities, whereas seasonality of influenza tended to be less marked in the tropical city. 3. High temperature was associated with increased mortality after influenza infection in Hong Kong, whereas relative humidity was an effect modifier for influenza in Guangzhou. No effect modification was found for Singapore. 4. Seasonal and environmental factors probably play a more important role than socioeconomic factors in regulating seasonality and disease burden of influenza. Further studies are needed in identifying the mechanism behind the regulatory role of environmental factors.

How to determine life expectancy change of air pollution mortality: a time series study.

BACKGROUND: Information on life expectancy (LE) change is of great concern for policy makers, as evidenced by discussions of the "harvesting" (or "mortality displacement") issue, i.e. how large an LE loss corresponds to the mortality results of time series (TS) studies. Whereas loss of LE attributable to chronic air pollution exposure can be determined from cohort studies, using life table methods, conventional TS studies have identified only deaths due to acute exposure, during the immediate past (typically the preceding one to five days), and they provide no information about the LE loss per death. METHODS: We show how to obtain information on population-average LE loss by extending the observation window (largest "lag") of TS to include a sufficient number of "impact coefficients" for past exposures ("lags"). We test several methods for determining these coefficients. Once all of the coefficients have been determined, the LE change is calculated as time integral of the relative risk change after a permanent step change in exposure. RESULTS: The method is illustrated with results for daily data of non-accidental mortality from Hong Kong for 1985 - 2005, regressed against PM10 and SO2 with observation windows up to 5 years. The majority of the coefficients is statistically significant. The magnitude of the SO2 coefficients is comparable to those for PM10. But a window of 5 years is not sufficient and the results for LE change are only a lower bound; it is consistent with what is implied by other studies of long term impacts. CONCLUSIONS: A TS analysis can determine the LE loss, but if the observation window is shorter than the relevant exposures one obtains only a lower bound.

Part 5. Public health and air pollution in Asia (PAPA): a combined analysis of four studies of air pollution and mortality.

BACKGROUND: In recent years, Asia has experienced rapid economic growth and a deteriorating environment caused by the increasing use of fossil fuels. Although the deleterious effects of air pollution from fossil-fuel combustion have been demonstrated in many Western nations, few comparable studies have been conducted in Asia. Time-series studies of daily mortality in Asian cities can contribute important new information to the existing body of knowledge about air pollution and health. Not only can these studies verify important health effects of air pollution in local regions in Asia, they can also help determine the relevance of existing air pollution studies to mortality and morbidity for policymaking and environmental controls. In addition, the studies can help identify factors that might modify associations between air pollution and health effects in various populations and environmental conditions. Collaborative multicity studies in Asia-especially when designed, conducted, and analyzed using a common protocol-will provide more robust air pollution effect estimates for the region as well as relevant, supportable estimates of local adverse health effects needed by environmental and public-health policymakers. SPECIFIC OBJECTIVES: The Public Health and Air Pollution in Asia (PAPA*) project, sponsored by the Health Effects Institute, consisted of four studies designed to assess the effects of air pollution on mortality in four large Asian cities, namely Bangkok, in Thailand, and Hong Kong, Shanghai, and Wuhan, in China. In the PAPA project, a Common Protocol was developed based on methods developed and tested in NMMAPS, APHEA, and time-series studies in the literature to help ensure that the four studies could be compared with each other and with previous studies by following an established protocol. The Common Protocol (found at the end of this volume) is a set of prescriptive instructions developed for the studies and used by the investigators in each city. It is flexible enough to allow for adjustments in methods to optimize the fit of health-effects models to each city's data set. It provides the basis for generating reproducible results in each city and for meta-estimates from combined data. By establishing a common methodology, factors that might influence the differences in results from previous studies can more easily be explored. Administrative support was provided to ensure that the highest quality data were used in the analysis. It is anticipated that the PAPA results will contribute to the international scientific discussion of how to conduct and interpret time-series studies of air pollution and will stimulate the development of high-quality routine systems for recording daily deaths and hospital admissions for time-series analysis. METHODS: Mortality data were retrieved from routine databases with underlying causes of death coded using the World Health Organization (WHO) International Classification of Diseases, 9th revision or 10th revision (ICD-9, ICD-10). Air quality measurements included nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter with aerodynamic diameter < or = 10 microm (PM10), and ozone (O3) and were obtained from several fixed-site air monitoring stations that were located throughout the metropolitan areas of the four cities and that met the standards of procedures for quality assurance and quality control carried out by local government units in each city. Using the Common Protocol, an optimized core model was established for each city to assess the effects of each of the four air pollutants on daily mortality using generalized linear modeling with adjustments for time trend, seasonality, and other time-varying covariates by means of a natural-spline smoothing function. The models were adjusted to suit local situations by correcting for influenza activity, autocorrelation, and special weather conditions. Researchers in Hong Kong, for example, used influenza activity based on frequency of respiratory mortality; researchers in Hong Kong and Shanghai used autoregressive terms for daily outcomes at lag days; and researchers in Wuhan used additional smoothing for periods with extreme weather conditions. RESULTS AND DISCUSSION: For mortality due to all natural (nonaccidental) causes at all ages, the effects of air pollutants per 10-microg/m3 increase in concentration was found to be higher in Bangkok than in the three Chinese cities, with the exception of the effect of NO2 in Wuhan. The magnitude of the effects for cardiovascular and respiratory mortality were generally higher than for all natural mortality at all ages. In addition, the effects associated with PM10 and O3 in all natural, cardiovascular; and respiratory mortality were found to be higher in Bangkok than in the three Chinese cities. The explanation for these three findings might be related to consistently higher daily mean temperatures in Bangkok, variations in average time spent outdoors by the susceptible populations, and the fact that less air conditioning is available and used in Bangkok than in the other cities. However, when pollutant concentrations were incorporated into the excess risk estimates through the use of interquartile range (IQR), the excess risk was more comparable across the four cities. We found that the increases in effects among older age groups were greater in Bangkok than in the other three cities. After excluding data on extremely high concentrations of PM10 in Bangkok, the effect estimate associated with PM10 concentrations decreased in Bangkok (suggesting a convex relationship between risk and PM10, where risk levels off at high concentrations) instead of increasing, as it did in the other cities. This leveling off of effect estimates at high concentrations might be related to differences in vulnerability and exposure of the population to air pollution as well as to the sources of the air pollutant. IMPLICATIONS OF THE STUDY: The PAPA project is the first coordinated Asian multicity air pollution study ever published; this signifies the beginning of an era of cooperation and collaboration in Asia, with the development of a common protocol for coordination, data management, and analysis. The results of the study demonstrated that air pollution in Asia is a significant public health burden, especially given the high concentrations of pollutants and high-density populations in major cities. When compared with the effect estimates reported in the research literature of North America and Western Europe, the study's effect estimates for PM10 were generally similar and the effect estimates for gaseous pollutants were relatively higher. In Bangkok, however, a tropical city where total exposures to outdoor pollution might be higher than in most other cities, the observed effects were greater than those reported in the previous (i.e., Western) studies. In general, the results suggested that, even though social and environmental conditions across Asia might vary, it is still generally appropriate to apply to Asia the effect estimates for other health outcomes from previous studies in the West. The results also strongly support the adoption of the global air quality guidelines recently announced by WHO.

Modelling the impact of population-based cytologic screening on cervical cancer incidence and mortality in Hong Kong: an age--period--cohort approach.

Cervical cancer incidence and mortality statistics in Hong Kong during 1972-2001 were examined to estimate the potential number of cancer cases that can be averted and years of life saved after the launch of an organised, population-based cytologic screening recall programme in 2004 with projections to 2016. Incidence rates under the status quo of opportunistic screening were projected by an age-period-cohort model, using maximum likelihood and Bayesian methods. Modelled rates were translated into numbers of cancer cases and deaths using mid-year population figures and age-period-specific mortality to incidence ratios. We applied International Agency for Research on Cancer risk reduction estimates for different screening strategies to these base case figures to estimate the number of incident cancers potentially averted and years of life saved attributable to organised screening incremental to the current status quo. The estimated numbers of cases projected to be preventable by the maximum likelihood (Bayesian) approach from 2002 to 2016 were 4226 (4176), 3778 (3728) and 2334 (2287) with organised screening every 1, 3 and 5 years, compared to haphazard screening currently. Correspondingly, 33,000 (32,800), 29,500 (29,300) and 18,200 (17,900) years of life could potentially be saved.

Binary latent variable modelling and its applicationin the study of air pollution in Hong Kong.

A binary latent variable is constructed to account for the correlation between multiple binary outcomes and is treated as a dependent variable in modelling for covariate effects. This modelling method is similar to the structural equation modelling. Three models are considered: (1) all covariates affecting the binary latent variable directly; (2) some covariates affecting the binary latent variable while other affecting the manifestation of the binary outcomes; and (3) no covariates are included. Gibbs sampling, a special case of the Markov Chain Monte Carlo method, is used to estimate the parameters in the models. Simulation studies show that this method is valid and reliable in estimating covariate effects. But Model (1) fitted the data best with lowest value in the deviance information criteria. The method is illustrated by applying it to the data analysis of an environmental air pollution study. The results show that air pollution (i.e. the most versus the least polluted district) (odds ratio 1.20; 95% confidence interval 0.97-1.49; p=0.102), smoking (relative to not smoking) (2.75; 2.21-3.41; p < 0.001) and mosquito coil use (relative to non-use) (1.27; 0.99-1.62; p=0.058) had an impact on the respiratory health of male adults in Hong Kong.

Trends in breast cancer incidence in Hong Kong between 1973 and 1999: an age-period-cohort analysis.

Hong Kong has the highest breast cancer incidence in Asia and studying secular changes in its rates may lead to hypotheses regarding disease aetiology and also predictions of future trends for China. We examined statistics from the Hong Kong Cancer Registry based on 26 566 cases of invasive breast cancer from 1973 to 1999. The trends in breast cancer incidence were studied using log-linear longitudinal models. We further analysed the independent effects of chronological age, time period and birth cohort on incidence trends using age-period-cohort modelling. The average annual per cent change of the age-standardised incidence was 3.6% during 1973-1999. Age-period-cohort modelling indicated the incidence development was predominantly a cohort effect, where the rise in relative risk was seemingly linear in successive birth cohorts, showing a 2-3-fold difference when comparing women born in the 1960's with those born around 1900. Our results suggest that direct and indirect consequences of westernisation may have been responsible for most of the observed increase in breast cancer incidence. As China moves towards a more westernised way of life, we can expect an emerging epidemic of breast cancer as Hong Kong's experience has demonstrated.

Rates of cesarean births in Hong Kong: 1987-1999.

BACKGROUND: High cesarean birth rates are an issue of international public health concern. The purpose of this paper was to examine the annual incidence and secular trend of cesarean births in Hong Kong and to correlate these rates with socioeconomic, demographic, and health indicators for the population since 1987. METHODS: This was a descriptive and ecologic study. Annual population rates of cesarean sections were estimated for 1987 from a population-based survey, and for 1993 through 1999 from government data sources. The number of excess cesarean sections was calculated for each year using the 15 percent upper limit as proposed by the World Health Organization. RESULTS: From 1987 to 1999 the overall annual cesarean section rate rose steadily from 16.6 to 27.4 per 100 hospital deliveries, resulting in a 65 percent increase over 12 years. The mean difference in rates of surgical delivery between public (mean(public) = 16.0%) and private (mean(private) = 43.4%) institutions was 27.4 percent (95% confidence interval (CI) = 24.1, 30.7; p < 0.001). CONCLUSIONS: This is the first systematic report of secular variations of cesarean delivery rates in Asia. The high rates and increasing trend represent an unnecessary excess risk for mothers and their infants. Various strategies combating high cesarean rates have been proposed and have succeeded elsewhere. Concerted action from health care professionals, public health authorities, the general population, and the media is urgently required to implement solutions to reduce the rate of cesarean delivery.